(bright music) >> Hello everyone and welcome back to AWS re:Invent, here in wonderful Las Vegas, Nevada. We're theCUBE. I am Savannah Peterson. Joined with my co-host, Dave Vellante. Day four, you look great. Your voice has come back somehow. >> Yeah, a little bit. I don't know how. I took last night off. You guys, I know, were out partying all night, but - >> I don't know what you're talking about. (Dave laughing) >> Well, you were celebrating John's birthday. John Furrier's birthday today. >> Yes, happy birthday John! >> He's on his way to England. >> Yeah. >> To attend his nephew's wedding. Awesome family. And so good luck, John. I hope you feel better, he's got a little cold. >> I know, good luck to the newlyweds. I love this. I know we're both really excited for our next guest, so I'm going to bring out, Lena Smart from MongoDB. Thank you so much for being here. >> Thank you for having me. >> How's the show going for you? >> Good. It's been a long week. And I just, not much voice left, so. >> We'll be gentle on you. >> I'll give you what's left of it. >> All right, we'll take that. >> Okay. >> You had a fireside chat, at the show? >> Lena: I did. >> Can you tell us a little bit about that? >> So we were talking about the Rise, The developer is a platform. In this massive theater. I thought it would be like an intimate, you know, fireside chat. I keep believing them when they say to me come and do these talks, it'll be intimate. And you turn up and there's a stage and a theater and it's like, oh my god. But it was really interesting. It was well attended. Got some really good questions at the end as well. Lots of follow up, which was interesting. And it was really just about, you know, how we've brought together this developer platform that's got our integrated services. It's just what developers want, it gives them time to innovate and disrupt, rather than worry about the minutia of management. >> Savannah: Do the cool stuff. >> Exactly. >> Yeah, so you know Lena, it's funny that you're saying that oh wow, the lights came on and it was this big thing. When when we were at re:Inforced, Lena was on stage and it was so funny, Lena, you were self deprecating like making jokes about the audience. >> Savannah: (indistinct) >> It was hilarious. And so, but it was really endearing to the audience and so we were like - >> Lena: It was terrifying. >> You got huge props for that, I'll tell you. >> Absolutely terrifying. Because they told me I wouldn't see anyone. Because we did the rehearsal the day before, and they were like, it's just going to be like - >> Sometimes it just looks like blackness out there. >> Yeah, yeah. It wasn't, they lied. I could see eyeballs. It was terrifying. >> Would you rather know that going in though? Or is it better to be, is ignorance bliss in that moment? >> Ignorance is bliss. >> Yeah, yeah yeah. >> Good call Savannah, right? Yeah, just go. >> The older I get, the more I'm just, I'm on the ignorance is bliss train. I just, I don't need to know anything that's going to hurt my soul. >> Exactly. >> One of the things that you mentioned, and this has actually been a really frequent theme here on the show this week, is you said that this has been a transformative year for developers. >> Lena: Yeah. >> What did you mean by that? >> So I think developers are starting to come to the fore, if you like, the fore. And I'm not in any way being deprecating about developers 'cause I love them. >> Savannah: I think everyone here does. >> I was married to one, I live with one now. It's like, they follow me everywhere. They don't. But, I think they, this is my opinion obviously but I think that we're seeing more and more the value that developers bring to the table. They're not just code geeks anymore. They're not just code monkeys, you know, churning out lines and lines of code. Some of the most interesting discussions I've had this week have been with developers. And that's why I'm so pleased that our developer data platform is going to give these folks back time, so that they can go and innovate. And do super interesting things and do the next big thing. It was interesting, I was talking to Mary, our comms person earlier and she had said that Dave I guess, my boss, was on your show - >> Dave: Yeah, he was over here last night. >> Yeah. And he was saying that two thirds of the companies that had been mentioned so far, within the whole gamut of this conference use MongoDB. And so take that, extrapolate that, of all the developers >> Wow. >> who are there. I know, isn't that awesome? >> That's awesome. Congrats on that, that's like - >> Did I hear that right now? >> I know, I just had that moment. >> I know she just told me, I'm like, really? That's - >> That's so cool. >> 'Cause the first thing I thought of was then, oh my god, how many developers are we reaching then? 'Cause they're the ones. I mean, it's kind of interesting. So my job has kind of grown from, over the years, being the security geek in the back room that nobody talks to, to avoiding me in the lift, to I've got a seat at the table now. We meet with the board. And I think that I can see that that's where the developer mindset is moving towards. It's like, give us the right tools and we'll change your world. >> And let the human capital go back to doing the fun stuff and not just the maintenance stuff. >> And, but then you say that, you can't have everything automated. I get that automation is also the buzzword of the week. And I get that, trust me. Someone has to write the code to do the automation. >> Savannah: Right. >> So, so yeah, definitely give these people back time, so that they can work on ML, AI, choose your buzzword. You know, by giving people things like queriable encryption for example, you're going to free up a whole bunch of head space. They don't have to worry about their data being, you know harvested from memory or harvested while at rest or in motion. And it's like, okay, I don't have to worry about that now, let me go do something fun. >> How about the role of the developer as it relates to SecOps, right? They're being asked to do a lot. You and I talked about this at re:Inforce. You seem to have a pretty good handle on it. Like a lot of companies I think are struggling with it. I mean, the other thing you said said to me is you don't have a lack of talent at Mongo, right? 'Cause you're Mongo. But a lot of companies do. But a lot of the developers, you know we were just talking about this earlier with Capgemini, the developer metrics or the application development team's metrics might not be aligned with the CSO's metrics. How, what are you seeing there? What, how do you deal with it within Mongo? What do you advise your customers? >> So in terms of internal, I work very closely with our development group. So I work with Tara Hernandez, who's our new VP of developer productivity. And she and her team are very much interested in making developers more productive. That's her job. And so we get together because sometimes security can definitely be seen as a blocker. You know, funnily enough, I actually had a Slack that I had to respond to three seconds before I come on here. And it was like, help, we need some help getting this application through procurement, because blah, blah, blah. And it's weird the kind of change, the shift in mindset. Whereas before they might have gone to procurement or HR or someone to ask for this. Now they're coming to the CSO. 'Cause they know if I say yes, it'll go through. >> Talk about social engineering. >> Exactly. >> You were talking about - >> But turn it around though. If I say no, you know, I don't like to say no. I prefer to be the CSO that says yes, but. And so that's what we've done. We've definitely got that culture of ask, we'll tell you the risks, and then you can go away and be innovative and do what you need to do. And we basically do the same with our customers. Here's what you can do. Our application is secure out of the box. Here's how we can help you make it even more, you know, streamlined or bespoke to what you need. >> So mobile was a big inflection point, you know, I dunno, it seems like forever ago. >> 2007. >> 2007. Yeah, iPhone came out in 2007. >> You remember your first iPhone? >> Dave: Yeah. >> Yeah? Same. >> Yeah. It was pretty awesome, actually. >> Yeah, I do too. >> Yeah, I was on the train to Boston going up to see some friends at MIT on the consortium that I worked with. And I had, it was the wee one, 'member? But you thought it was massive. >> Oh, it felt - >> It felt big. And I remember I was sitting on the train to Boston it was like the Estella and there was these people, these two women sitting beside me. And they were all like glam, like you and unlike me. >> Dave: That's awesome. >> And they, you could see them like nudging each other. And I'm being like, I'm just sitting like this. >> You're chilling. >> Like please look at my phone, come on just look at it. Ask me about it. And eventually I'm like - >> You're baiting them. >> nonchalantly laid it on the table. And you know, I'm like, and they're like, is that an iPhone? And I'm like, yeah, you want to see it? >> I thought you'd never ask. >> I know. And I really played with it. And I showed them all the cool stuff, and they're like, oh we're going to buy iPhones. And so I should have probably worked for Apple, but I didn't. >> I was going to say, where was your referral kickback on that? Especially - >> It was a little like Tesla, right? When you first, we first saw Tesla, it was Ray Wong, you know, Ray? From Pasadena? >> It really was a moment and going from the Blackberry keyboard to that - >> He's like want to see my car? And I'm like oh yeah sure, what's the big deal? >> Yeah, then you see it and you're like, ooh. >> Yeah, that really was such a pivotal moment. >> Anyway, so we lost a track, 2007. >> Yeah, what were we talking about? 2007 mobile. >> Mobile. >> Key inflection point, is where you got us here. Thank you. >> I gotchu Dave, I gotchu. >> Bring us back here. My mind needs help right now. Day four. Okay, so - >> We're all getting here on day four, we're - >> I'm socially engineering you to end this, so I can go to bed and die quietly. That's what me and Mary are, we're counting down the minutes. >> Holy. >> That's so sick. >> You're breaking my heart right now. I love it. I'm with you, sis, I'm with you. >> So I dunno where I was, really where I was going with this, but, okay, there's - >> 2007. Three things happened. >> Another inflection point. Okay yeah, tell us what happened. But no, tell us that, but then - >> AWS, clones, 2006. >> Well 2006, 2007. Right, okay. >> 2007, the iPhone, the world blew up. So you've already got this platform ready to take all this data. >> Dave: Right. >> You've got this little slab of gorgeousness called the iPhone, ready to give you all that data. And then MongoDB pops up, it's like, woo-hoo. But what we could offer was, I mean back then was awesome, but it was, we knew that we would have to iterate and grow and grow and grow. So that was kind of the three things that came together in 2007. >> Yeah, and then Cloud came in big time, and now you've got this platform. So what's the next inflection point do you think? >> Oh... >> Good question, Dave. >> Don't even ask me that. >> I mean, is it Edge? Is it IOT? Is there another disruptor out there? >> I think it's going to be artificial intelligence. >> Dave: Is it AI? >> I mean I don't know enough about it to talk about it, to any level, so don't ask me any questions about it. >> This is like one of those ignorance is bliss moments. It feels right. >> Yeah. >> Well, does it scare you, from a security perspective? Or? >> Great question, Dave. >> Yeah, it scares me more from a humanity standpoint. Like - >> More than social scared you? 'Cause social was so benign when it started. >> Oh it was - >> You're like, oh - I remember, >> It was like a yearbook. I was on the Estella and we were - >> Shout out to Amtrak there. >> I was with, we were starting basically a wikibond, it was an open source. >> Yeah, yeah. >> Kind of, you know, technology community. And we saw these and we were like enamored of Facebook. And there were these two young kids on the train, and we were at 'em, we were picking the brain. Do you like Facebook? "I love Facebook." They're like "oh, Facebook's unbelievable." Now, kids today, "I hate Facebook," right? So, but social at the beginning it was kind of, like I say, benign and now everybody's like - >> Savannah: We didn't know what we were getting into. >> Right. >> I know. >> Exactly. >> Can you imagine if you could have seen into the future 20 years ago? Well first of all, we'd have all bought Facebook and Apple stock. >> Savannah: Right. >> And Tesla stock. But apart from, but yeah apart from that. >> Okay, so what about Quantum? Does that scare you at all? >> I think the only thing that scares me about Quantum is we have all this security in place today. And I'm not an expert in Quantum, but we have all this security in place that's securing what we have today. And my worry is, in 10 years, is it still going to be secure? 'Cause we're still going to be using that data in some way, shape, or form. And my question is to the quantum geniuses out there, what do we do in 10 years like to retrofit the stuff? >> Dave: Like a Y2K moment? >> Kind of. Although I think Y2K is coming in 2038, isn't it? When the Linux date flips. I'll be off the grid by then, I'll be living in Scotland. >> Somebody else's problem. >> Somebody else's problem. I'll be with the sheep in Glasgow, in Scotland. >> Y2K was a boondoggle for tech, right? >> What a farce. I mean, that whole - >> I worked in the power industry in Y2K. That was a nightmare. >> Dave: Oh I bet. >> Savannah: Oh my God. >> Yeah, 'cause we just assumed that the world was going to stop and there been no power, and we had nuclear power plants. And it's like holy moly. Yeah. >> More than moly. >> I was going to say, you did a good job holding that other word in. >> I think I was going to, in case my mom hears this. >> I grew up near Diablo Canyon in, in California. So you were, I mean we were legitimately worried that that exactly was going to happen. And what about the waste? And yeah it was chaos. We've covered a lot. >> Well, what does worry you? Like, it is culture? Is it - >> Why are you trying to freak her out? >> No, no, because it's a CSO, trying to get inside the CSO's head. >> You don't think I have enough to worry about? You want to keep piling on? >> Well if it's not Quantum, you know? Maybe it's spiders or like - >> Oh but I like spiders, well spiders are okay. I don't like bridges, that's my biggest fear. Bridges. >> Seriously? >> And I had to drive over the Tappan Zee bridge, which is one of the longest, for 17 years, every day, twice. The last time I drove over it, I was crying my heart out, and happy as anything. >> Stay out of Oakland. >> I've never driven over it since. Stay out of where? >> Stay out of Oakland. >> I'm staying out of anywhere that's got lots of water. 'Cause it'll have bridges. >> Savannah: Well it's good we're here in the desert. >> Exactly. So what scares me? Bridges, there you go. >> Yeah, right. What? >> Well wait a minute. So if I'm bridging technology, is that the scary stuff? >> Oh God, that was not - >> Was it really bad? >> It was really bad. >> Wow. Wow, the puns. >> There's a lot of seems in those bridges. >> It is lit on theCUBE A floor, we are all struggling. I'm curious because I've seen, your team is all over the place here on the show, of course. Your booth has been packed the whole time. >> Lena: Yes. >> The fingerprint. Talk to me about your shirt. >> So, this was designed by my team in house. It is the most wanted swag in the company, because only my security people wear it. So, we make it like, yeah, you could maybe have one, if this turns out well. >> I feel like we're on the right track. >> Dave: If it turns out well. >> Yeah, I just love it. It's so, it's just brilliant. I mean, it's the leaf, it's a fingerprint. It's just brilliant. >> That's why I wanted to call it out. You know, you see a lot of shirts, a lot of swag shirts. Some are really unfortunately sad, or not funny, >> They are. >> or they're just trying too hard. Now there's like, with this one, I thought oh I bet that's clever. >> Lena: It is very cool. Yes, I love it. >> I saw a good one yesterday. >> Yeah? >> We fix shit, 'member? >> Oh yeah, yeah. >> That was pretty good. >> I like when they're >> That's a pretty good one. >> just straightforward, like that, yeah yeah. >> But the only thing with this is when you're say in front of a green screen, you look as though you've got no tummy. >> A portal through your body. >> And so, when we did our first - >> That's a really good point, actually. >> Yeah, it's like the black hole to nothingless. And I'm like wow, that's my soul. >> I was just going to say, I don't want to see my soul like that. I don't want to know. >> But we had to do like, it was just when the pandemic first started, so we had to do our big presentation live announcement from home. And so they shipped us all this camera equipment for home and thank God my partner knows how that works, so he set it all up. And then he had me test with a green screen, and he's like, you have no tummy. I'm like, what the hell are you talking about? He's like, come and see. It's like this, I dunno what it was. So I had to actually go upstairs and felt tip with a magic marker and make it black. >> Wow. >> So that was why I did for two hours on a Friday, yeah. >> Couldn't think of another alternative, huh? >> Well no, 'cause I'm myopic when it comes to marketing and I knew I had to keep the tshirt on, and I just did that. >> Yeah. >> In hindsight, yes I could have worn an "I Fix Shit" tshirt, but I don't think my husband would've been very happy. I secure shit? >> There you go, yeah. >> There you go. >> Over to you, Savannah. >> I was going to say, I got acquainted, I don't know if I can say this, but I'm going to say it 'cause we're here right now. I got acquainted with theCUBE, wearing a shirt that said "Unfuck Kubernetes," 'cause it was a marketing campaign that I was running for one of my clients at Kim Con last year. >> That's so good. >> Yeah, so - >> Oh my God. I'll give you one of these if you get me one of those. >> I can, we can do a swapskee. We can absolutely. >> We need a few edits on this film, on the file. >> Lena: Okay, this is nothing - >> We're fallin' off the wheel. Okay, on that note, I'm going to bring us to our challenge that we discussed, before we got started on this really diverse discussion that we have had in the last 15 minutes. We've covered everything from felt tip markers to nuclear power plants. >> To the darkness of my soul. >> To the darkness of all of our souls. >> All of our souls, yes. >> Which is perhaps a little too accurate, especially at this stage in the conference. You've obviously seen a lot Lena, and you've been rockin' it, I know John was in your suite up here, at at at the Venetian. What's your 30 second hot take? Most important story, coming out of the show or for you all at Mongo this year? >> Genuinely, it was when I learned that two-thirds of the customers that had been mentioned, here, are MongoDB customers. And that just exploded in my head. 'Cause now I'm thinking of all the numbers and the metrics and how we can use that. And I just think it's amazing, so. >> Yeah, congratulations on that. That's awesome. >> Yeah, I thought it was amazing. >> And it makes sense actually, 'cause Mongo so easy to use. We were talking about Tengen. >> We knew you when, I feel that's our like, we - >> Yeah, but it's true. And so, Mongo was just really easy to use. And people are like, ah, it doesn't scale. It's like, turns out it actually does scale. >> Lena: Turns out, it scales pretty well. >> Well Lena, without question, this is my favorite conversation of the show so far. >> Thank you. >> Thank you so much for joining us. >> Thank you very much for having me. >> Dave: Great to see you. >> It's always a pleasure. >> Dave: Thanks Lena. >> Thank you. >> And thank you all, tuning in live, for tolerating wherever we take these conversations. >> Dave: Whatever that was. >> I bet you weren't ready for this one, folks. We're at AWS re:Invent in Las Vegas, Nevada. With Dave Vellante, I'm Savannah Peterson. You're washing theCUBE, the leader for high tech coverage.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to HPE. Discover 2022. My name is Dave Lanta. I'm here with my co-host John fur. John we've been watching the evolution of H HP to HPE. We've seen GreenLake when Antonio Neri, I called it. I called it burn the boats. He goes, no, no, no, it wasn't burn the boats. I said, well, okay, burn the bridges. But it was all in on as a service on, on GreenLake. And we're gonna talk about that. Brad Shapiro is here. He's the vice president and managing director of the enterprise business at HPE financial services. Brad. Good to see him. Good to see >>You as well. >>Yeah, you guys got it all started. When, when Antonio kinda laid down, the gauntlet said, this is where we're going. Let's make it happen now. Cause the first place he turned I would imagine is the financial services said, okay, how do we start this today? Can you help us? And they take us back to that >>And yeah, sure. So, you know, uh, yeah, HP financial services, um, it's kind of a foundational element cuz when you think about it, asset management is really what we're doing here. And I know asset management's a, a big word, right? And it can mean lots of things to, to different people. Um, in this context, uh, we started looking at how do customers manage assets over the life cycle and a lot of customers while they were interested in a consumption model and looking at GreenLake for their private cloud, they were certainly looking at public cloud for certain workloads and then maybe even traditional data center for other activities that, that they're running. So it's really that hybrid environment. Uh, but they were stuck going well, Hey, I'm in a CapEx model today. How do I get out of CapEx and really get into this hybrid model? >>And that's where asset management comes in. So one of the, the biggest initial focus is, and we continue to have that focus. We call it our accelerated migration offer and it's really us going in and acquiring the customer assets, moving it on the HPE balance sheet and then figuring out what are we gonna do with those assets, which are gonna stay in use under a consumption model, which are excess. And we can put through our, uh, asset up cycling process, we monetize the majority of that, put that back into reuse and then maybe a small amount gets recycled. So, so really focused on the assets and accelerating customers transition to GreenLake. Did you >>See, or are you seeing a difference between like Le traditional leasing customers who already have kind of on that model versus like what you just described as sort of the, the CapEx was more complicated, you gotta get, I presume procurement involved the legal issues and was there a lot less, was it less friction with the, the leasing customers? Well, >>You know, I, I look at leasing and financing, very similar to CapEx. It's, it's a much more traditional model versus this new as a service experience. Um, so if, if they were in a leasing model, we could convert those leases into GreenLake. I wouldn't say one was any more difficult than the other. Yeah. Um, they were both really traditional mindset, um, and not really looking at a consumption model. So I think we had our fair share of both. And I think we, we have and are able to address both customers moving in into a consumption >>Mode. Right. How does this tie into sustainability? Because you know, we have on one end of the spectrum, the, the high end sustainability, you know, the, the science and sure. And the behind it, tactically speaking companies still now want to operate in this kind of, there's a sustainable angle here. Yeah. Talk about that piece of it. How does that tie in obviously consumption versus CapEx you're building, you're not building, what, what does that thread through the sustainability angle? >>Yeah. So, so first let me just say sustainability is really important to our customers. Um, and, and we're seeing it all over and it is real. Um, the good thing is that you can get business value out of the solutions and have a more sustainable model. So when I think about, and I talk to customers about sustainability, uh, there's a number of fronts they're focused on one, their customers believe it's important, right? So, so they're focused on making sure they're driving sustainable models. Uh, I've seen an increasing number of customers, both commercial and public sector have sustainability requirements in their tenders, in their RFPs. And you have to be able to, to comply with those. Um, second, uh, they, they look at it and go, how do I attract talent? It's increasingly important for them to attract talent. And then really if you, because >>They wanna work for a mission driven company that's >>Sustainable. Absolutely. Absolutely. And, and the third area is investors. You know, the investment community is now looking at ESG and whole and you know, certainly environmental impacts, um, in where they're making an investment. So quick personal story, I was talking, uh, to a friend of mine who works for a hedge fund and he was telling me over the last year, they've hired a whole team. That's focused on just doing analysis of companies, ESG initiatives, determining where they're gonna invest their money. So it's, it's a wall street thing now. So this is real from a number of angles where, where sustainability has an impact. Now, how we play in that. Um, clearly when you go to a GreenLake consumption model, the idea is improving utilization of the asset. So driving higher utilization means you need less assets. You know, over time, the, the secret is we're gonna sell you less, right? >>You're gonna have less assets, but you're gonna have higher utilization. That's good for the environment where HPE Fs comes in is when those assets are done. We put those assets back into reuse. So we have a remark, we have remarketing facilities, one in, in Andover, mass, one in kin Scotland. And then we have 80 different facilities. We have partnerships around the world and our focus is how do we drive more reuse, 85% of the assets we get back, go into reuse. And when you look at servers and PCs and things like that, it's over 95% go into reuse. So a real focus on reuse is good for the environment as well. And then needless to say, the new technology that goes into a GreenLake deal, we're seeing like 30% energy savings coming, coming out of those environments. So all really good stuff related to it's >>Interesting. I mean, a couple points there is one is, you know, Benoff kind of got it all started pre pandemic. He was out talking about, you know, sustainability and ESG. And a lot of people were like, no way. It's all about bottom line profits. And so he was ahead of that. And I guess, you know, back to at least you were, oh, you were always in the residual value game, but now it's a little different, isn't it? Absolutely. It's, it's it's yes. You gotta figure out what the value of that asset's gonna be, but also there's a sustainability aspect of it as >>Well. Yeah, absolutely. And the, the pretty cool thing here is while you drive sustainability, we're also seeing customers that, that go into GreenLake. Um, we had a good example with Kern county, a 42% savings over their CapEx environment when they moved to GreenLake. So it was better for the environment and significant savings. So you can have kind of like have your cake and eat it too. You, you get better environmental, uh, impacts and you're getting better bottom line, uh, performance. >>It's a business case there too do. Now we kind of, I was talking upfront about the, the early days of GreenLake where, you know, they were, it was a financial model. Yeah. And now it's evolving to actually a technology model. We heard Alma with the platform. How has that, or has that changed the way that financial services your >>Group >>Yeah. Approaches the, the, the market. >>Yeah. So, um, yeah, that's a great point. You know, when people talk about GreenLake, they think about the old days. And, and look, I've been around a while. I remember the flex capacity, right? Yeah, of course this isn't flex capacity. I mean, the platform's amazing and it really starts to bring to life the whole thought, when we talk about hybrid, right, there are workloads sure. They might belong best in the public cloud. Right. There, there are workloads that belong best in the private cloud, under the HPE GreenLake model. And there are still workloads that customers may say, Hey, look, I've got legacy applications. I'm gonna continue to run them in a traditional data center. And so from an H P E Fs perspective, you know, we look at this, not as a leasing and financing company, we're looking at this on how do we leverage the customer's existing assets? >>How do we create incremental budget using those existing assets? And then what kind of model best serves that workload? And then how do you optimize the capacity and the spend on that? So, you know, an interesting note in the past year, we put 500 million back into customer budgets by just leveraging their existing it estate. And, and it does, it's not all HPE product, you know, we're, we're, we're monetizing third party products in the data center, in the network, in the workplace. So we can really look at, we call it any tech any time, anywhere we look at all the technology and really assess what's the best way to leverage that investment. Yeah. And, and get the most out of >>It. Yeah. I mean, it's really evolved from just recycling assets for profit, but integrating the business model into the value proposition, the core value proposition in GreenLake. That's great innovation. Um, and, and congratulations on that. Sure. My, my question for you is more kind of zooming out at the market. Mm-hmm <affirmative>, from your perspective in financial services at HPE, what has the pandemic proven to you guys? How has it changed? How you guys work and how has it changed the customer environment? Cuz you mentioned assets. I think real estate. Oh no. One's going back to work. Yeah, no one's been in the office. How has the market changed with hybrids as a steady state now coming outta the pandemic? What are customers doing with the assets? What are some of the trends that you're seeing in the customer base? >>Yeah. So, so look, I'll give you my personal perspective of what I think about as a business leader. And when I talk to customers, I think we're all thinking about the same thing. So I start with experience, what experience do I wanna create for my customers and very closely linked to that, my colleagues, right? So it, the, the people working in our organization, what experience am I creating for them? So they can in turn, create that experience for partners and customers externally. So experience is one thing. The second is innovation, right? We spend a lot of time thinking about what's next? Where do we want to go? What's the innovation and more and more that innovation is all digital, right? So digital transformation is huge within my organization. And it's huge within all of our customers. Dave, I think the last time we talked, I was in my living room on a little laptop screen and zoom and, and I think I use the analogy E every business is now a digital business, even my pizza shop in jerseys. >>Yeah. Right. I mean, everything was online curbside pickup. So what I'm finding is the, the trends in terms of how to leverage technology is how do you create that customer experience? And then how does digital now blend as we're coming out of the pandemic? And, and you're, you know, now able to go into restaurants and stores, how do you blend digital with that in person experience and maybe leverage the best of both. Right. And, and how do you do that in a seamless way to really give customers choice and give them that smooth, seamless experience. So that, that's what I see happening. And you know, what we are trying to do with our asset management plays with the financial modeling we do is how do we get more of that spend going to innovation versus maintenance. And, and that's a big key because, you know, you have to be fast. So I talk about innovation. I talk about customer experience, speed to market. I mean, you know, and the bar keeps getting higher, right? It's like, as soon as you think you're fast, you're slow. We, because you have to keep, it all keeps rolling. >>We heard yesterday on the cube from, uh, one of the HP point, next executives said, you gotta perform and transform >>At the >>Same time at the same time. And you gotta know where the people are gonna land. Absolutely. And how the assets are gonna be distributed. >>And to your point, Brad, you know, from our virtual interview, you're so right. I mean, every business has to be a digital business. And you know, my, my personal story, John, you know, my brother Richie was the executive chef at legal seafood. Right. Pandemic. So then that was a, a place you wanted to go to that restaurant, famous restaurant in Boston when they reopened, they weren't ready. Right. They didn't have the digital story together. They ended up having to, we were just at Smith and Linsky, they ended up selling to Smith and Wilensky's oh, and you, you drive around, you see a lot of these retail businesses is shut down. Yeah. Right. And so, okay. So we're, they weren't able to get through that, you know, cross that chasm in digital transformation. Yeah. A lot of businesses were able to and make it a tailwind. >>Yeah. And, and look, the other thing I think all businesses are focused on right now, uh, with the labor market is talent. And, and so when you think about all of these things tying together, you want to drive, uh, you know, innovation. You want to drive your digital transformation. You wanna make that environmentally sustainable. And, and I think all of that, if you start putting all that together, those are the companies that are gonna attract the talent in the marketplace. And, and really there there's a battle for talent and >>You wanna make it profitable. Uh, Brad bureau. Thanks so much for you. Great to see you face to face. >>Yeah. Likewise. Thanks. Thanks. >>All right. Keep it right there, John. And I will be back. We're wrapping up day three of HPE, discover 2022. You're watching the cube.

>> Announcer: From around the globe, it's theCUBE! With digital coverage of IBM Think 2021. Brought to you by IBM. >> Well welcome everyone as theCUBE continues our IBM Think series. It's a pleasure to have you with us here on theCUBE. I'm John Walls, and we're joined today by Brian Loveys who is the Director of Offering Management for Customer and Employee Care Applications at IBM in the Data and AI Division. So, Brian, thanks for joining us from Ottawa, Canada. Good to see you today. >> Yeah, great to be here, John. And looking forward to the session today. >> Which, by the way, I've learned Ottawa are the home of the world's largest ice skating rink. I doubt we get into that today, but it is interesting food for thought. So, Brian, first off, let's just talk about the AI landscape right now. I know IBM obviously very heavily invested in that. Just in terms of how you see this currently in terms of enterprise adoption, what people are doing with it, and just how you would talk about the state of the industry right now. >> You know, it's a really interesting one, right? I think if you look at it, you know, different companies, different industries, frankly, are at different stages of their AI journey, right? I think for me personally, what was really interesting was, and we're all going through the pandemic right now, but last year with COVID-19 in the March timeframe, it was really interesting to see the impact, frankly, in the space that I play predominantly in around customer care, right? When the pandemic hit, immediately call centers, contact centers got flooded with calls, right? And so it created a lot of problems for organizations. But what was interesting to me is it accelerated a lot of adoption of AI to organizations that typically lag in technology, right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things, and trying to, you know, communicate out information. So it was really interesting to see those organizations, frankly, accelerate really, really quickly, right? And if you actually, you know, talk to those organizations now, I think one of the most interesting things to me in thinking about it and talking to them now is like, hey, you know, we can do this, right? AI is really not that complicated. It can be simplified, we can take advantage of it and all of those types of things, right? So I think for me, you know, I kind of see different industries at sort of different levels, but I think with COVID in particularly, you know, and frankly not just COVID, but even digital transformation alongside COVID is really driving a lot of AI in an accelerated manner. The other thing that I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right? There's a tremendous opportunity to innovate in this space. And I think we all know that, you know, data is continually being created every single day. And as more people become even more digitalized, there's more and more data being created. Like it's how do you start to harness that data more effectively, right, in your business every day. And frankly, I think we're just scratching the surface on it. And I think tremendous amount of opportunity as we move forward. >> Yeah, you really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disruptor, right, but in this case it was purely, or really largely environment, you know, that was driving this disruption, right, forcing people to make these adoption moves and transitions maybe a little quicker than they expected. Well, so because of that, because maybe somebody had to speed up their timetable for deployments and what have you, what kind of challenges have they run into then, where, because as you describe it, it's not been the more organic kind of decision-making that might be made sometimes, situation dictated it. So what have you seen in terms of challenges, you know, barriers, or just a little more complexity, perhaps, for some people who're just now getting into the space because of the environment you were talking about? >> I think a lot of this is like, you know, people don't know where to get started, right, a lot of the time, or how AI can be applied. So a lot of this is going to be about education in terms of what it can and cannot do. And then it all depends on the use cases you're talking about, right? So if I think about, you know, building out machine learning models and those types of things, right, you know, the set of challenges that people will typically face in these types of things are, you know, how do I, you know, collect all the data that I need to go build these models, right? How do I organize that data? You know, how do I get the skillsets needed to ultimately, you know, take advantage of all of that data to actually then apply to where I need it in my business, right? So a lot of this is, you know, people need to understand those concepts or those pieces to ultimately be successful with AI. And you know, what IBM is doing right here, and I'll kind of, this will be a key theme throughout this conversation today is, you know, how do you sort of lower the time to value to get there across that spectrum, but also, you know, frankly, the skills required along the way as well? But a lot of it is like, people don't know what they don't know at the end of the day. >> Well, let me ask you about your AI play then. A lot of people involved in this space, as you well know, competition's pretty fierce and pretty widespread. There's a deep bench here. In terms of IBM though, what do you see as kind of your market differentiator then? You know, what do you think sets you apart in terms of what you're offering in terms of AI deployments and solutions? >> No, that's a great question. I think it's a multifaceted answer, frankly. The first thing I'll kind of talk through a little bit, right, is really around our platform and our framework, right? We kind of refer to as our AI ladder, but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning a bit earlier, right? If you think about, you know, AI is really about supplying the right data into AI, and then being able to infuse it to where you need it to go, right? So to do that, you need a lot of the underlying information architecture to do that, right? So you need the ability to collect the data. You need the ability to organize the data. You need the ability to build out these models or analyze the data, right? And then of course you need to be able to infuse that AI wherever you need it to be, right? And so we have a really nice integrated platform that frankly can be deployed on any cloud, right, so we get the flexibility of that deployment model with that integrated platform. And if you think about it, we also have built, right, you know, sort of these industry-leading AI applications that sit on top of that platform and that underlying infrastructure, right? So Watson Assistant, right, our conversational AI which we'll talk probably a little bit more on this conversation, right? Watson Discovery focused on, you know, intelligent document processing, right, AI search type applications. We've got these sort of market-leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm, right, that continues to invest and funnel innovations into our product platform and into our product portfolio, right? I think many people are aware of Project Debater we took on some of the top debaters in the world, right? But research ultimately is very much tied, right, and even, you know, some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just- >> I'm sorry go ahead, please. >> Go ahead, sorry. >> No, no, you go, (laughs) I interrupted, you go ahead. >> Don't worry, I was just going to say, the other two things I'll say like, you know, I'm saying this right, but we've got a lot of sort of proof points in around it, right, so if you talk about the scale, right, the number of customers, the number of case studies, the number of references across the board, right, in around AI at IBM it is significant, right? And not only that, but we've got a lot of, sort of I'll say industry and third-party industry recognition, right? So think about most people are aware of sort of Gartner Magic Quadrants, right, and we're the leader almost across the board, right, or a leader across the board. So, you know, cloud AI developer service, insight engines, machine learning, go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well, if that makes sense. >> Yeah, sure does. You know, we hear a lot about conversational AI and, you know, with online chat bots and voice assistance, and a myriad applications in that respect. Let's talk about conversational right now. Some people think is a little narrow, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI element to what you're talking about at IBM and how that is coming into play. And perhaps is a pretty big growth sector in this space. >> Yeah, I think, again, I talk about scratching the surface, early innings, you'll see that theme a lot too. And I think this is another area around that, right? So, listen, let's talk about the broader side. Let's first talk about where conversational AI is typically applied, right? So you see it in customer service. That's the obvious place where I've seen the most deployments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. You can think about, you know, lead qualification for example, right. You know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions, how can I schedule console? All those things can be automated using, right, conversational AI, but organizations don't want these sort of points solutions across the customer journey. What they're ultimately looking for is a single assistant to kind of, you know, front that particular customer. So what if I do come on from a lead qual perspective, but really I'm not there for lead qual, I'm actually a customer, and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, right? So on the customer side where we see the conversational AI going is really sort of covering that whole gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine not just, you know, the website and the chat on the website, but also, right, across your messaging channels, across your phone, right? And not just that, but you also want to be able to have a really nice experience around, hey maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play, right? Maybe that's easier to sign up for a particular offer, or do some authentication, or whatever it might be, right? So to sort of be able to switch between the channels is really, really going to become more important in terms of a seamless experience as you do kind of go through it, right- >> So let's talk about customers- >> Oh, go ahead sir. >> Yeah, you talked about customers a little bit, and you mentioned case studies, but I hope we can get into some specifics, if you can give us some examples about people, companies with whom you've worked and some success that you've had in that respect. And I think maybe the usual suspects come to mind. I think about finance, I think about healthcare, but you said, "Hey buddy, but customer call issues, you know, service centers, that kind of thing would certainly come into play," but can you give us an idea or some examples of deployments and how this is actually working today? >> Oh, absolutely, right? So I think you were kind of mentioning, you were talking about sort of industries that are relevant, right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer side of it, right? So clearly in financial services, banks, insurance are clearly obvious ones. Telecommunication, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in, right? And so you'll see different use cases in those industries as well, right? So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to NatWest in Scotland. So they started out with customer service, right? So dealing with personal banking questions through their website. What's interesting, and you'll see this with a lot of these use cases is they will start small, right, with a single use case, but they'll start to expand from there. So for example, NatWest, right, they're starting with personal banking, but they're now expanding to other areas of the business across that customer journey, right? So that's a great example of where we've seen it. Cardinal Health, right, because we're not dealing with customers in terms of external customers, but dealing with internal customers, right, from an IT help desk standpoint. So it's not always external customers. Oftentimes, frankly, it can be employees, right? So they are using it through an IDR system, right? So through over the phone, right, so I can call, instead of getting that 1-800 number, I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their help desk. So, and they started really, really small, right? They started with, you know, simple things like password resets, but that represented a tremendous amount of volume that ultimately hit at their call centers. So NatWest is a great example. CIBC, another bank in Canada, Toronto, is a great example. And the nice thing about what CIBC is doing and they're a big, you know, we have four big banks here in Canada. What CIBC do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money, or all those types of things, or check your balance or whatever it might be. So putting a nice, simple interface on some of those common, transactional things that you would do with a bank as well. >> You know, before I let you go, I'd like to hit just a buzzword we hear a lot of these days, natural language processing, NLP. All right, so NLP, define that in terms of how you see it and how is it being applied today? Why does NLP matter, and what kind of differences is it making? >> Wow, natural language processing is a loaded term as a buzzword, I completely agree. I mean, listen, at the 50,000 foot level, natural language processing is really about understanding language, right? So what do I mean by that? So let's use the simple conversational example we just talked about. If somebody's asking about, you know, "I'd like to reset my password," right? You have to be able to understand, well what is the intent behind what that user is trying to do, right? They're trying to reset a password, right? So being able to understand that inquiry that user has that's coming in and being able to understand what the intent is behind it. That's sort of one key aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing, the importance of extracting certain things that you need to know. And again, using the conversational AI side, just for a minute, to give a simple example. If I said, "You know what, I need to reset my password." I know what the intent is, I want to reset a password, but, right, I don't know which password I'm trying to reset. Right, and so this is where sort of you have to be able to extract objects, and we call them entities a lot of the time and sort of the (indistinct) or lingo. But you got to be able to extract those elements. So, you know, I want to reset my ATM password. Great, right, so I know what they're trying to do, but I also need to extract that it's the ATM password that I'm trying to do. So that's one sort of key angle, natural language processing, and there's a lot of different AI techniques to be able to do those types of things. I'll also tell you though, there's a lot around the content side of the fence as well. So you can imagine how like a contract, right, and there were thousands of these contracts, and some of your terms may change. You know, how do you know, out of those thousands of contracts where the problems are, where I need to start looking, right? So another sort of key area of natural language processing is looking at the content itself, right? Can I look at these contracts and automatically understand that this is an indemnity clause, right? Or this is an obligation, right? Or those types of things, right, and being able to sort of pick those things out, so that I can help deal with those sort of contract-processing things. So that's sort of a second dimension. The third dimension I'll kind of give around this is really around, you can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and nouns, and those types of things, but maybe I want to know in an analytics use case with customers, you know, what is the sentiment and, you know, analyzing social media posts or whatever it might be, what's the sentiment that people have around my product or service. So natural language process, if you think about it at the real high level is really about how do I understand language, but there's a variety of sort of ways to do that, if that makes sense. >> Yeah, no sure, and I think there are a lot of people out there saying, "Yeah, the sooner we can identify exasperation (laughs) the better off we're going to be, right, in handling the problems." So, it's hard work, but it's to make our lives easier, and congratulations for your fine work in that space. And thanks for joining us here on theCUBE. We appreciate the time today, Brian. >> Thank you very much. >> You bet, Brian Loveys, he's talking to us from IBM, talking about conversational AI and what it can do for you. I'm John Walls, thanks for joining us here on theCUBE. (upbeat music) ♪ Dah, deeah ♪ ♪ Dah, dee ♪ (chimes ringing)

>>from >>Around the globe. It's the cube with digital coverage of IBM think 2021 brought to you by IBM >>Well welcome everyone is the cube continues or IBM Thanks series. It's a pleasure to have you with us here on the cube. I'm john walls and we're joined today by brian loves who is the director of offering management for customer and employee care applications in the at IBM in the data and AI division. So brian, thanks for joining us from Ottawa Canada, good to see you today. >>Yeah, great to be here john I'm looking forward to the session today >>which by the way I've learned Ottawa is the home of the world's largest ice skating rink. I doubt we'll get into that today, but it is interesting food for thought. Uh so brian first off, let's just talk about um the Ai landscape right now. I know IBM obviously very heavily invested in that uh just in terms of how you see this currently as in terms of enterprise adoption, what people are doing with it and and just how you would talk about the state of the industry right now, >>you know, it's a really interesting one, right? I think if you look at it, you know different companies, different industries frankly are at different stages of their Ai journey, right? Um I think for me personally what was really interesting was, and we're all going through the pandemic right now, but last year with covid 19 in the March timeframe, it was really interesting to see the impact, frankly in the space that I played predominantly in around customer care, right? When the pandemic hit immediately call centers, contact centres got flooded with calls, right? And so it created a lot of problems for organizations. But it was interesting to me is it accelerated a lot of adoption of ai to organizations that typically lag and technology. Right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things and trying to communicate and communicate out information. So it was really interesting to see those organizations frankly accelerate really, really quickly, right? And if you actually talk to those organizations now, I think one of the most interesting things to me and thinking about it and talking to them now is like, hey, you know, we can do this right, AI is really not that complicated, it can be simplified, we can take advantage of it and all of those types of things. Right? So I think for me, you know, I kind of see different industries that sort of different levels, but I think with Covid in particularly, you know, and frankly not just Covid, but even digital transformation alongside Covid is really driving a lot of ai in an accelerated manner. The other thing I'll kind of I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right, there is a tremendous opportunity innovating in the space and I think we all know that you know data is continually being created every single day and as more people become even more digitalized, there's more and more data being created. Like how do you start to harness that data more effectively, right in your business every day? And frankly I think we're just scratching scratching the surface on it and I think tremendous amount of opportunity as we move forward. >>Yeah, he really is really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disrupter, right? But in this case it was purely really, largely environment that was driving this disruption, right, forcing people to to make these adoption moves and transitions maybe a little quicker than they expected. So because of that, because maybe somebody had to speed up their timetable for deployments and what have you what what kind of challenges have they run into them? Where because, as you describe it, it's not been the more organic kind of decision making that might be made, sometimes situation dictated it. So what have you seen in terms of challenges, barriers or just a little more complexity perhaps for some people who are just not getting into the space because of the environment you were talking about? >>I think a lot of this is like people don't know where to get started, right, a lot of the time or how ai can be applied. So a lot of this is going to be a bad education in terms of what it can and cannot do, and then it all depends on the use cases you're talking about, right? So if I think about, you know, building a machine learning models and those types of things right? You know, this set of challenges that people will typically face in these types of things are, you know, how do I collect all the data that I need to go build these models? Right? How do I organize that data? Um you know, how do I get the skill sets needed to ultimately, you know, take advantage of all that data to actually then apply to where I needed in my business? Right, So a lot of this is, you know, people need to understand, you know, those concepts are those pieces um to ultimately be successful with AI and you know what IBM is doing right here and I'll kind of this will be a key theme through this conversation today, is how do you sort of lower the time to value, to get there across that spectrum, but also, you know, frankly the skills >>required along the way as >>well, but a lot of it is like people don't know what they don't know at the end of the day. Mhm. >>Well, let me ask you about about your AI play then, a lot of people involved in this space, as you well know, you know, competitions pretty fierce and pretty widespread, there's a deep bench here um in terms of IBM know, what do you see is kind of your market different differentiator then, you know, what what do you think set you apart in terms of what you're offering in terms of AI deployments and solutions? >>No, that's a great question. I think it's a multifaceted answer, frankly. Um the first thing I'll kind of talk through a little bit right, is really around our platform and our our framework, right? We could refer to as our air ladder, um but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning earlier, right? If you think about, you know, AI is really about supplying the right data into A I. And then being able to infuse it to where you needed to go. Right? So to do that, you need a lot of the underlying information architecture to do that, Right? So you need the ability to collect the data, you need the ability to organize the data, you need the ability to to build out these models, right? Or analyze the data and then of course you need to be able to infuse that ai wherever you need it to be. Right. And so we have a really nice integrated platform that frankly can be deployed on any cloud. Right? So we got the flexibility that deployment model with that in greater platform. And you think about it? We also have built right, you know, sort of these industry leading Ai applications that sit on top of that platform and that underlying infrastructure. Right? So Watson assistant, Right. Our conversational AI, which we'll talk probably a little bit more on this conversation. Right, Watson discovery focus on, you know, intelligent document processing, right. AI search type applications. We've got these sort of market leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm right, that continues to invest and funnel innovations into our product platform and into our product portfolio. Right? I think many people are aware of project debater, we took on some of the top debaters in the world, right? But research ultimately is very much tied, right? And even some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, Right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just go ahead, >>Please go ahead. three. No, no. You know, I interrupted you. Go ahead. >>No, I was just gonna say that the other two things, I'll say it like, you know, I'm saying this right, but we've got a lot of sort of proof points and around it. Right? So, if you talk about the scale right? The number of customers, the number of case studies, a number of references across the board, right? In around AI AT IBM It is significant, Right? Um, and not only that, but we've got a lot of sort of, I'll say industry and third party industry recognition. Right? So think about most people are aware of sort of Gartner magic quadrants, right? And we're the leader almost across the board, Right? Or a leader across the board. So cloudy I developer service inside engines, machine learning go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well. That makes sense. >>Yeah, it sure does. You know, we're hearing a lot about conversational AI and, you know, with online chat bots and voice assistance and a myriad applications in that respect. Let's talk about conversational right now. Some people think it's little narrow, but, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI um, uh, element um, to what you're talking about at IBM and how that is coming into play and, and perhaps is a pretty big growth sector in this space. >>Yeah, I think again, I talked about scratching the surface early innings. You'll see that theme a lot too. And I think this is another area around that. So listen, let's talk about the broader side. Let's first talk about where conversation always typically applied. Right? So you see it in customer service, that's the obvious place we're seeing the most appointments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. If you think about, you know, lead qualification, for example, right? How can, you know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions? How can I schedule console? All those things can be automated using great conversationally. I, the organizations don't want these sort of point solutions across the customer journey. What we're ultimately looking for is a single assistant to kind of, you know, front right, that particular customer. So what if I do come on from a legal perspective, but really I'm not here for legal. I'm actually a customer and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, Right? So on the customer side where we see the conversation like, hey, I going and it's really kind of covering that full gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine right now, not just, you know, the website and the chat on the website, but also right across their messaging channels, right across your phone. Right. And not just that, but you also want to be a really nice experience around, hey, maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play. Right? Maybe that's easier to sign up for a particular offer or do some authentication or whatever might be, right. So to sort of be able to sort of switch between the channels, it's really, really going to become more important in this sort of sort of seamless experience as you just kind of go through it. Right? >>So you're coming by customers. Yeah. >>You talked about customers a little bit and you mentioned case studies, but can we get, I hope we can get into some specifics. You can give us some examples about people, companies with whom you've worked and and some success that you've had that respect. And I think maybe the usual suspects come to mind about finance. I might health care, but you said anybody with customer call issues, service centers, that kind of thing would certainly come into play. But can you give us an idea or some examples of deployments and how this is actually working today? >>Oh, absolutely. Right. So I think you kind of mentioned you become sort of industries that are relevant. Right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer sort of side to it. Right? So clearly in financial services, banks, insurance, and clearly obvious ones telecommunications, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in. Right? So you'll see different use cases in those industries as well. Right. So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to natwest Open Scotland. Um So they started out with customer service. Right? So dealing with personal banking questions through their website, what's interesting and you'll see this with a lot of these use cases is they will start small, right with a single use case that they'll start to expand from there. So, for example, >>natwest right there, starting with they started with personal banking, but they're not expanding to other areas of the business across that customer journey. Right. So it's a great example of where we've seen it. Cardinal Health Right. We're not dealing with customers in terms of external customers but dealing with internal customers right from the help that standpoint. So it's not always external customers. Oftentimes frankly it can be employees. Right? So they are using it right through an I. V. R. System. Right? So through over the phone. Right. So I can call instead of getting that 1 800 number. I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their health does so. And they started really, really small, right? They started with simple things like password resets but that represented a tremendous amount of volume but ultimately headed their cost cost centers. So not West is a great example. C I B C. Another bank in Canada Toronto is a great example and the nice thing about what CNBC is doing and there are big, you know, we have four big banks here in Canada, what have you seen do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money or over those types of things or check your balance or whatever it might be. So putting a nice simple interface on some of those common transactional things that you >>would do with the bank as well, >>you know, before I let you go, uh I'd like to hit this of buzz where we hear a lot of these days natural language processing. NLP Alright, so, so NLP define that in terms of how you see it and and how is it being applied today? Why why does NLP matter? And what kind of difference is it making? >>Wow, that's a loaded natural language processing. There's a loaded term in a buzzword. I completely agree. I mean listen, at the 50,000 ft level, natural language processing is really about understanding length, Right? So what do I mean by that? So let's use the simple conversational example. We just talked about if somebody is asking about, I'd like to reset my password right? You have to be able to understand what is the intent behind what that user is trying to do right there? Trying to reset a password, right? So being able to understand that inquiry that the user has that's coming in and being able to understand what the intent is behind it. >>That's sort of one, you know, aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing the importance, extracting certain things that you need to know. And again using the conversational ai side, just for a minute to give a simple example if I said you know what I need to reset my password, I know what the intent is. I want to reset a password but Right I don't know which password I'm trying to reset. Right? So this is where you have to be able to extract objects and we call them entities a lot of time in sort of the ice bake or lingo but you've got to be able to extract those elements. So you know I want to reset my A. T. M. Password. Great. Right so I know what they're trying to do but I also need to extract that it's the A. T. M. Password that I'm trying to do. So that's one sort of key angle of natural language processing and there's a lot of different techniques to be able to do those types of things. I'll also tell you though there's a lot around the content side of the fence as well, right? So you can imagine having a contract, right? And there are thousands of these contracts and some of your terms may change. How do you know, out of those thousands of contracts where the problems are, where I need to start looking, Right? So another sort of keep key area of natural language processing is looking at the content itself. Can I look at these contracts and automatically understand that this is an indemnity clause, Right? And this is an obligation, right? Or those types of things, right? And be able to sort of pick pick those things out so that I can help deal with those sort of contract processing things. That's sort of a second dimension. The third dimensional kind of kind of give around this is really around. You can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and downs and those types of things. But maybe I want to know and analytics use case with customers. Um you know, what is the sentiment and you know, analyzing social media posts or whatever it might be. What's the sentiment that people have around my product or service? So naturally this process, if you think about it, the real high level is really about how do I understand language? But there's a variety of sort of ways to do that if that makes sense? >>Yeah, sure. And I think there's a lot of people out there saying, yeah, the sooner we can identify exasperation, the better off we're going to be right and handling the problems. But it's hard work but it's to make our lives easier and congratulations for your fine work in that space. And thanks for joining us here on the cube. We appreciate the time. Today, brian, >>thank very much. >>You bet BRian Levine is talking to us from IBM talking about conversational Ai and what it can do for you. I'm john Walsh, thanks for joining us here on the cube. Mhm. >>Mhm.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon Angle. Hi, I'm stupid, man. And welcome back to the Cube on Cloud. We're talking about developers. And while so many people remember the mean from 2010 of Steve Balmer jumping around on stage development developers and developers, uh, many people know what really important is really important about developers. They probably read the 2013 book called The New King Makers by Stephen O. Grady. And I'm really happy to welcome to the program. Rachel Stevens, who is an industry analyst with Red Monk who was co founded by the aforementioned Stephen O. Grady. Rachel, Great to see you. Thank you so much for joining us. >>Thank you so much for having me. I'm excited to be here. >>Well, I've had the opportunity, Thio read some of what you've done. We've interacted on social media. We've got to talk events back when we used to do those in people. And >>I'm so >>glad that you get to come on the program especially. You were the ones I reached out. When we have this developer track, um, if you could just give our audience a little bit about your background. You know, that developer cred that you have Because as I joke, I've got a closet full of hoodies. But, you know, I'm an infrastructure guy by training I've been learning about, you know, containers and serverless and all this stuff for years. But I'm not myself much of developer. I've touched a thing or two in the years. >>Yeah. So happy to be here. Red Monk has been around since 2002 and have kind of been beating that developer drum ever since then, kind of as the company, The founder, Stephen James, notice that the decision making that developers was really a driver for what was actually ending up in the Enterprise. And as even more true, as cloud came onto, the scene is open source exploded, and I think it's become a lot more of a common view now. But in those early days, it was probably a little bit more of a controversial opinion, but I have been with the firm for coming up on five years now. My work is an industry analyst. We kind of help people understand, bottoms up technology, adoption trends, so that that's where I spend my time focusing is what's getting used in the enterprise. Why, what kind of trends are happening? So, yeah, that's where we all come from. That's the history of Red Monk in 30 seconds. >>Awesome. Rachel, you talk about the enterprise and developers For the longest time. I just said there was this huge gap you talk about. Bottoms up. It's like, well, developers use the tools that they want If they don't have to, they don't pay for anything. And the general I t. And the business sides of the house were like, I don't know, We don't know what those people in the corner we're doing, you know, it's important and things like that. But today it feels like that that's closed a bunch. Where are we? In your estimation, you know, our developers do they have a clear seat at the table? The title we have for this is whether the Enterprise Developer is its enterprise development oxymoron. In 2020 and 2021 >>I think enterprise developers have a lot more practical authority than people give them credit for, especially if you're kind of looking at that old view of the world where everything is driven by a buyer decision or kind of this top down purchasing motion. And we've really seen that authority of what is getting used and why change a lot in the last year. In the last decade, even more of people who are able to choose the tools that meet the job bring in tools, regardless of whether they maybe have that official approval through the right channels because of the convenience of trying to get things up and running. We are asking developers to do so much right now and to go faster and thio shifting things left. And so the things that they are responsible for incorporating into the way they are building APS is growing. And so, as we are asking developers to do more and to do more quickly, um, the tools that they need to do those, um, tasks to get these APS built is that the decision making us fall into them? This is what I need. This is what needs to come in, and so we're seeing. Basically, the tools that enterprise is air using are the tools that developers want to be using, and they kind of just find their way into the enterprise. >>Now I want to key off what you were talking about. Just developers were being asked to do Mawr and Mawr. We've seen these pendulum swings in technology. There was a time where it was like, Well, I'll outsource it because that'll be easier and maybe it'll be less expensive. And number one we found it necessarily. It wasn't necessarily cheaper. And number two, I couldn't make changes, and I didn't understand what was happening. So when when I talked to Enterprises today, absolutely. I need to have skills that's internally. I need to be able to respond to things fast, and therefore I need skills that I need people that can build what they have. What what do you see? What are those skill sets that are so important today? Uh, you know, we've talked so many times over the years is to you know, there's there's the skills gap. We don't have enough data scientists. We don't have enough developers way. We don't have any of these things. So what do we have and where things trending? >>Yeah, it's It's one of those things for developers where they both have probably the most full tool set that we've seen in this industry in terms of things that are available to them. But it's also really hard because it also indicates that there is just this fragmentation at every level of the stack. And there's this explosion of choice and decisions that is happening up and down the stack of how are we going to build things? And so it's really tricky to be a developer these days and that you are making a lot of decisions and you are wiring a lot of things together and you have to be able to navigate a lot of things. E think. One of the things that is interesting here is that we have seen the phrase like Full stack developer really carried a lot of panache, maybe earlier this decade and has kind of fallen away. Just because we've realized that it's impossible for anybody to be ableto spanned this whole broad spectrum of all of the things we're asking people to dio. So we're seeing this explosion of choice, which is meaning that there is a little bit more focused and where developers are trying to actually figure out what is my niche. What is it that I'm supposed to focus on. And so it's really just this balancing of act of trying to see this big picture of how to get this all put together and also have this focused area realizing that you have to specialize at some point. >>Rachel is such a great point there. We've actually seen that Cambrian explosion of developer tools that are out there. If you go to the CFCF landscape and look at everything out there or goto any of your public cloud providers, there's no way that anybody even working for those companies no good portion of the tools that are out there so nobody could be a master of everything. How about from a cloud standpoint, you know, there is the discussion of, you know what do I shift? Left What? You know, Can I just say, Okay, this piece of it, it could be a manage service. I don't need to think about it versus what skills that I need to have in house. What is it that's important. And obviously, you know, a zoo analyst. We know it varies greatly across companies, but you know what? What are some of those top things that we need to make sure that enterprises have skill set and the tools in house that they should understand. And what can they push off to their platform of choice? >>Yeah, I think your comment about managed services is really pressing because one of the trends that we're watching closely, it's just this rise of manage services. And it kind of ties back into the concept you had before about like, what an I team. That's they have, like the Nicholas Carr. I t doesn't matter, and we're pushing this all the way. And then we realized, Oh, we've got to bring that all back. Um, but we also realize that we really want as enterprises want to be spending our time doing differentiated work and wiring together, your entire infrastructure isn't necessarily differentiated for a lot of companies. And so it's trying to find this mix of where can I push my abstraction higher or to find a manage service that can do something for me? And we're seeing that happen in all levels of the stack. And so what we're seeing is this rise of composite APS where we're going to say, Okay, I'm gonna pull in back end AP ice from a whole bunch of tools like twilio or stripe or all zero where algo Leah, all of those things are great tools that I can incorporate into my app. And I can have this great user, um, interface that I can use. And then I don't have to worry quite so much about building it all myself. But I am responsible for wiring at all together. So I think it's that wire together set of interest that is happening for developers as the tool set that they are spending a lot of time with. So we see the manage services being important. Um played an important role in how absent composed, and it's the composition of that APs that is happening internally. >>What one of the one of the regular research items that I see a red monk is you know what languages you know. Where are the trends going? There's been relative stability, but then something's changed. You know, I look at the tools that you mentioned Full stack developer. I talked to a full stack developer a couple of years ago, and he's like like like terror form is my life and I love everything and I've used it forever. And that was 18 months, Andi. I kind of laugh because it's like, OK, I managed. I measure a lot of the technology that I used in the decades. Um, not that await. This came out six months ago and it's kind of mature. And of course, you know, C I C d. Come on. If it's six weeks old, it's probably gone through a lot of generations. So what do you see? Do you have any research that you can share as to looking forward? What are the You know what the skill sets we need? How should we be training our force? What do >>we need to >>be looking at in this kind of next decade of cloud? >>Yeah. So when when you spoke about languages, we dio a semi annual review of language usage as a sign on get hub and in discussion as seen on stack overflow, which we fully recognize is not a perfect representation of how these languages are used in the broader world. But those air data sets that we have access to that are relatively large and open eso just before anyone writes me angry letters that that's not the way that we should be doing it, Um, but one of the things that we've seen over time is that there is a lot of relative stability in those top tier languages in terms of how they are used, and there's some movement at the bottom. But the trends we're seeing where the languages are moving is type safety and having a safer language and the communities that are building upon other communities. So things like, um, we're seeing Scotland that is able to kind of piggyback off of being a jvm based language and having that support from Google. Or we're seeing typescript where it can piggyback off of the breath of deployment of JavaScript, things like that. So those things where were combining together multiple trends that developers are interested in the same time combined with an ecosystem that's already rich and full. And so we're seeing that there's definitely still movement in languages that people are interested in, but also, language on its own is probably pretty stable. So, like as you start to make language choices as a developer, that's not where we're seeing a ton of like turnover language frameworks on the other hand, like if you're a JavaScript developer and all of a sudden there's just explosion of frameworks that you need to choose from, that may be a different story, a lot more turnover there and harder to predict. But language trends are a little bit more stable over >>time, changing over time. You know, Boy, I I got to dig into, you know, relatively Recently I went down like the jam stack. Uh, ecosystem. I've been digging into a serverless for a number of years. What's your take on that? There's certain people. I talked to him. They're like, I don't even need to be a code. Or I could be a marketing person. And I can get things done when I talked to some developers there like a citizen developers. They're not developers. Come on, you know, I really need to be able to do this, so I'll give you your choices, toe. You know, serverless and some of these trends to kind of ext fan. You know who can you know? Code and development. >>Yeah. So for both translate jam stack and serve Ellis, One of the things that we see kind of early in the iteration of a technology is that it is definitely not going to be the right tool for every app. And the number of APS that they approach will fit for will grow as the tool develops. And you add more functionality over time and all of these platforms expand the capability, but definitely not the correct tool choice in every case. That said, we do watch both of those areas with extreme interest in terms of what this next generation of APS can look like and probably will look like in a lot of cases. And I think that it is super interesting to think about who gets to build these APs, because I e. I think one of the things that we probably haven't landed on the right language yet is what that what we should call these people because I don't think anyone associates themselves as a low code person. Like if you're someone from marketing and all of a sudden you can build something technical, that's really cool, and you're excited about that. Nobody else on your team could build. You're not walking around saying I am a low code marketing person like that, that that's that's that's demeaning. Like you're like. No, I'm technical. I'm a technical market, or look what I just did. And if you're someone who codes professionally for a living like and you use a low code tool to get something out the door quickly and >>you don't >>wanna demean and said, Oh, that was I did a low code that just like everybody, is just trying to solve problems. And everybody, um, is trying to figure out how to do things in the most effective way possible and making trade offs all the time. And so I don't think that the language of low code really is anything that resonates with any of the actual users of low code tools. And so I think that's something that we as an industry need toe work on finding the correct language because it doesn't feel like we've landed there yet. >>Yeah, Rachel, what? Want to get your take on just careers for developers now to think about in 2020 everyone is distributed. Lots of conversations about where we work. Can we bring the remote? Many of the developers I talked to already were remote. I had the chance that interview that the head of remote. Forget lab. They're over 1000 people and they're fully remote. So, you know, remote. Absolutely a thing for developers. But if you talk about careers, it is no longer, you know. Oh, hey, here's my CV. It's I'm on git Hub. You can see the code I've done. We haven't talked about open source yet, so give us your take on kind of developers today. Career paths. Andi. Kind of the the online community there. >>Yeah, this could be a whole own conversation. We'll try to figure out my points. Um, so I think one of the things that we are trying to figure out in terms of balance is how much are we expecting people to have done on the side? It's like a side project Hustle versus doing, exclusively getting your job done and not worrying too much about how many green squares you have on your get hub profile. And I think it's a really emotional and fraught discussion and a lot of quarters because it can be exclusionary for people saying that you you need to be spending your time on the side working on this open source project because there are people who have very different life circumstances, like if you're someone who already has kids or you're doing elder care or you are working another job and trying to transition into becoming a developer, it's a lot to ask. These people toe also have a side hustle. That said, it is probably working on open source, having an understanding of how tools are done. Having this, um, this experience and skills that you can point to and contributions you can point Teoh is probably one of the cleaner ways that you can start to move in the industry and break through to the industry because you can show your skills two other employers you can kind of maybe make your way in is a junior developer because you worked on a project and you make those connections. And so it's really still again. It's one of those balancing act things where there's not a perfect answer because there really is to correct sides of this argument. And both of those things are true. At the same time where it's it's hard to figure out what that early career path maybe looks like, or even advancing in a career path If you're already a developer, it's It's tricky. >>Well, I want to get your take on something to you know, I think back to you know, I go back a decade or two I started working with about 20 years ago. Back in the crazy days were just Colonel Daughter Warg and, you know, patches everywhere and lots of different companies trying to figure out what they would be doing on most of the people contributing to the free software before we're calling it open source. Most of the time, it was their side Hustle was the thing they're doing. What was their passion? Project? I've seen some research in the last year or so that says the majority of people that are contributing to open source are doing it for their day job. Obviously, there's a lot of big companies. There's plenty of small companies. When I goto the Linux Foundation shows. I mean, you've got whole companies that are you know, that that's their whole business. So I want to get your take on, you know, you know, governance, you know, contribution from the individual versus companies. You know, there's a lot of change going on there. The public cloud their impact on what's happening open source. What are you seeing there? And you know what's good? What's bad? What do we need to do better as a community? >>Yeah. E think the governance of open source projects is definitely a live conversation that we're having right now about what does this need to look like? What role do companies need to be having and how things are put together is a contribution or leadership position in the name of the individual or the name of the company. Like all of these air live conversations that are ongoing and a lot of communities e think one of the things that is interesting overall, though, is just watching if you're if you're taking a really zoomed out view of what open source looks like where it was at one point, um, deemed a cancer by one of the vendors in the space, and now it is something that is just absolutely an inherent part of most well tech vendors and and users is an important part of how they are building and using software today, like open source is really an integral tool. And what is happening in the enterprise and what's being built in the enterprise. And so I think that it is a natural thing that this conversation is evolving in terms of what is the enterprises role here and how are we supposed to govern for that? And e don't think that we have landed on all the correct answers yet. But I think that just looking at that long view, it makes sense that this is an area where we are spending some time focusing >>So Rachel without giving away state secrets. We know read Monk, you do lots of consulting out there. What advice do you give to the industry? We said we're making progress. There's good things there. But if we say okay, I wanna at 2030 look back and say, Boy, this is wonderful for developers. You know, everything is going good. What things have we done along the way? Where have we made progress? >>Yeah, I think I think it kind of ties back to the earlier discussion we were having around composite APS and thinking about what that developer experience looks like. I think that right now it is incredibly difficult for developers to be wiring everything together and There's just so much for developers to dio to actually get all of these APs from source to production. So when we talk with our customers, a lot of our time is spent thinking, How can you not only solve this individual piece of the puzzle, but how can you figure out how to fit it into this broader picture of what it is the developers air trying to accomplish? How can you think about where your ATF, It's not on your tool or you your project? Whatever it is that you are working on, how does this fit? Not only in terms of your one unique problem space, but where does this problem space fit in the broader landscape? Because I think that's going to be a really key element of what the developer experience looks like in the next decade. Is trying to help people actually get everything wired together in a coherent way. >>Rachel. No shortage of work to do there really appreciate you joining us. Thrilled to have you finally as a cube. Alumni. Thanks so much for joining. >>Thank you for having me. I appreciate it. >>All right. Thank you for joining us. This is the developer content for the cube on cloud, I'm stew minimum, and as always, thank you for watching the Cube.

>>Hello. I'm Professor Toru Suzuki Cherif cardiovascular medicine on associate dean of the College of Life Sciences at the University of Leicester in the United Kingdom, where I'm also director of the Lester Life Sciences accelerator. I'm also honorary consultant cardiologist within our university hospitals. It's part of the national health system NHS Trust. Today, I'd like to talk to you about our Lester Clinical Data Science Initiative. Now brief background on Lester. It's university in hospitals. Lester is in the center of England. The national health system is divided depending on the countries. The United Kingdom, which is comprised of, uh, England, Scotland to the north, whales to the west and Northern Ireland is another part in a different island. But national health system of England is what will be predominantly be discussed. Today has a history of about 70 years now, owing to the fact that we're basically in the center of England. Although this is only about one hour north of London, we have a catchment of about 100 miles, which takes us from the eastern coast of England, bordering with Birmingham to the west north just south of Liverpool, Manchester and just south to the tip of London. We have one of the busiest national health system trust in the United Kingdom, with a catchment about 100 miles and one million patients a year. Our main hospital, the General Hospital, which is actually called the Royal Infirmary, which can has an accident and emergency, which means Emergency Department is that has one of the busiest emergency departments in the nation. I work at Glen Field Hospital, which is one of the main cardiovascular hospitals of the United Kingdom and Europe. Academically, the Medical School of the University of Leicester is ranked 20th in the world on Lee, behind Cambridge, Oxford Imperial College and University College London. For the UK, this is very research. Waited, uh, ranking is Therefore we are very research focused universities as well for the cardiovascular research groups, with it mainly within Glenn Field Hospital, we are ranked as the 29th Independent research institution in the world which places us. A Suffield waited within our group. As you can see those their top ranked this is regardless of cardiology, include institutes like the Broad Institute and Whitehead Institute. Mitt Welcome Trust Sanger, Howard Hughes Medical Institute, Kemble, Cold Spring Harbor and as a hospital we rank within ah in this field in a relatively competitive manner as well. Therefore, we're very research focused. Hospital is well now to give you the unique selling points of Leicester. We're we're the largest and busiest national health system trust in the United Kingdom, but we also have a very large and stable as well as ethnically diverse population. The population ranges often into three generations, which allows us to do a lot of cohort based studies which allows us for the primary and secondary care cohorts, lot of which are well characterized and focused on genomics. In the past. We also have a biomedical research center focusing on chronic diseases, which is funded by the National Institutes of Health Research, which funds clinical research the hospitals of United Kingdom on we also have a very rich regional life science cluster, including med techs and small and medium sized enterprises. Now for this, the bottom line is that I am the director of the letter site left Sciences accelerator, >>which is tasked with industrial engagement in the local national sectors but not excluding the international sectors as well. Broadly, we have academics and clinicians with interest in health care, which includes science and engineering as well as non clinical researchers. And prior to the cove it outbreak, the government announced the £450 million investment into our university hospitals, which I hope will be going forward now to give you a brief background on where the scientific strategy the United Kingdom lies. Three industrial strategy was brought out a za part of the process which involved exiting the European Union, and part of that was the life science sector deal. And among this, as you will see, there were four grand challenges that were put in place a I and data economy, future of mobility, clean growth and aging society and as a medical research institute. A lot of the focus that we have been transitioning with within my group are projects are focused on using data and analytics using artificial intelligence, but also understanding how chronic diseases evolved as part of the aging society, and therefore we will be able to address these grand challenges for the country. Additionally, the national health system also has its long term plans, which we align to. One of those is digitally enabled care and that this hope you're going mainstream over the next 10 years. And to do this, what is envision will be The clinicians will be able to access and interact with patient records and care plants wherever they are with ready access to decision support and artificial intelligence, and that this will enable predictive techniques, which include linking with clinical genomic as well as other data supports, such as image ing a new medical breakthroughs. There has been what's called the Topol Review that discusses the future of health care in the United Kingdom and preparing the health care workforce for the delivery of the digital future, which clearly discusses in the end that we would be using automated image interpretation. Is using artificial intelligence predictive analytics using artificial intelligence as mentioned in the long term plans. That is part of that. We will also be engaging natural language processing speech recognition. I'm reading the genome amusing. Genomic announced this as well. We are in what is called the Midland's. As I mentioned previously, the Midland's comprised the East Midlands, where we are as Lester, other places such as Nottingham. We're here. The West Midland involves Birmingham, and here is ah collective. We are the Midlands. Here we comprise what is called the Midlands engine on the Midland's engine focuses on transport, accelerating innovation, trading with the world as well as the ultra connected region. And therefore our work will also involve connectivity moving forward. And it's part of that. It's part of our health care plans. We hope to also enable total digital connectivity moving forward and that will allow us to embrace digital data as well as collectivity. These three key words will ah Linkous our health care systems for the future. Now, to give you a vision for the future of medicine vision that there will be a very complex data set that we will need to work on, which will involve genomics Phanom ICS image ing which will called, uh oh mix analysis. But this is just meaning that is, uh complex data sets that we need to work on. This will integrate with our clinical data Platforms are bioinformatics, and we'll also get real time information of physiology through interfaces and wearables. Important for this is that we have computing, uh, processes that will now allow this kind of complex data analysis in real time using artificial intelligence and machine learning based applications to allow visualization Analytics, which could be out, put it through various user interfaces to the clinician and others. One of the characteristics of the United Kingdom is that the NHS is that we embrace data and captured data from when most citizens have been born from the cradle toe when they die to the grave. And it's important that we were able to link this data up to understand the journey of that patient. Over time. When they come to hospital, which is secondary care data, we will get disease data when they go to their primary care general practitioner, we will be able to get early check up data is Paula's follow monitoring monitoring, but also social care data. If this could be linked, allow us to understand how aging and deterioration as well as frailty, uh, encompasses thes patients. And to do this, we have many, many numerous data sets available, including clinical letters, blood tests, more advanced tests, which is genetics and imaging, which we can possibly, um, integrate into a patient journey which will allow us to understand the digital journey of that patient. I have called this the digital twin patient cohort to do a digital simulation of patient health journeys using data integration and analytics. This is a technique that has often been used in industrial manufacturing to understand the maintenance and service points for hardware and instruments. But we would be using this to stratify predict diseases. This'll would also be monitored and refined, using wearables and other types of complex data analysis to allow for, in the end, preemptive intervention to allow paradigm shifting. How we undertake medicine at this time, which is more reactive rather than proactive as infrastructure we are presently working on putting together what's it called the Data Safe haven or trusted research environment? One which with in the clinical environment, the university hospitals and curated and data manner, which allows us to enable data mining off the databases or, I should say, the trusted research environment within the clinical environment. Hopefully, we will then be able to anonymous that to allow ah used by academics and possibly also, uh, partnering industry to do further data mining and tool development, which we could then further field test again using our real world data base of patients that will be continually, uh, updating in our system. In the cardiovascular group, we have what's called the bricks cohort, which means biomedical research. Informatics Center for Cardiovascular Science, which was done, started long time even before I joined, uh, in 2010 which has today almost captured about 10,000 patients arm or who come through to Glenn Field Hospital for various treatments or and even those who have not on. We asked for their consent to their blood for genetics, but also for blood tests, uh, genomics testing, but also image ing as well as other consent. Hable medical information s so far there about 10,000 patients and we've been trying to extract and curate their data accordingly. Again, a za reminder of what the strengths of Leicester are. We have one of the largest and busiest trust with the very large, uh, patient cohort Ah, focused dr at the university, which allows for chronic diseases such as heart disease. I just mentioned our efforts on heart disease, uh which are about 10,000 patients ongoing right now. But we would wish thio include further chronic diseases such as diabetes, respiratory diseases, renal disease and further to understand the multi modality between these diseases so that we can understand how they >>interact as well. Finally, I like to talk about the lesser life science accelerator as well. This is a new project that was funded by >>the U started this January for three years. I'm the director for this and all the groups within the College of Life Sciences that are involved with healthcare but also clinical work are involved. And through this we hope to support innovative industrial partnerships and collaborations in the region, a swells nationally and further on into internationally as well. I realized that today is a talked to um, or business and commercial oriented audience. And we would welcome interest from your companies and partners to come to Leicester toe work with us on, uh, clinical health care data and to drive our agenda forward for this so that we can enable innovative research but also product development in partnership with you moving forward. Thank you for your time.

>> announcer: From around the globe, it's theCUBE, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi everyone, welcome back to theCUBE's coverage, we're from HPE Discover Virtual Experience conference, HPE Discover, physical event, a gathering that happens every year. This year we're doing it virtually with HPE as everyone is kind of sheltering in place. And of course, we've got the best guests, the executives from HPE, their customers, practitioners, developers, we're talking to them all. I'm John for the host with theCUBE. We're here with John Schultz, the Chief Legal and Administrative Officer for HPE. Thank you for joining me today. Great to have you. >> My pleasure, thanks for having me. >> So you're in a unique position, I see you oversee the legal and administrative office of HPE. You've been there from when it was one big company and then two. >> Yep. >> You've seen some transformations over the years, (laughs) and you've seen in many different use cases right now, we're living in one that's pretty significantly historic, a lot of unrest of recent, but the pandemic itself is upon us. And the reality of what's happening cannot be ignored anymore. The disruption that's happened, no one forecasted this. They forecasted hurricanes and tsunamis, but not, pandemics. So these outages, is it issues? Now they have to come out of this. Your customers have to come out of this with a restructuring, a reinvention and a growth strategy. This is truly a forced transformation. What's your thoughts? >> Yeah, no, clearly unprecedented times, but at the same time, I think our perspective is that this is only accelerating the underlying trends that were already in the market. It starts with the fact that more and more people were working from home, and more and more data is going to live on the edge. And therefore, you need systems that can essentially handle that data and make that data into actual insights to fuel your business. And so clearly that trend we think is only accelerating. We also think the trend is accelerating with respect to the fact that people want to get out of the business of buying and operating IT infrastructure in a traditional sense. They want to move to the consumption of IT as a service. They want to focus less on operations and again, more on taking the data and driving those insights for their business. So all of these trends that have been out there for the last 12, 24, 36 months, I think are just accelerating. And this confluence of events is, therefore, making what we're doing at HPE and the transformation that we're leading all the more critical. >> So I want to get your thoughts, and I want to unpack the impact of how your role at HPE kind of reflects into the real marketplace with your customers. And I bring that up because we're have been covering the DevOps movement for over a decade, and it's been always on the fringe and with the cloud native and all the app development has been great, but network operations, IT operations, security operations, these are operational functions that don't have the cavalier fast and loose kind of approach. And legal usually is involved. Administration involve policies, and some say blockers, but it's not anymore. You're the Chief Legal and Administrative of HPE. Talk about what your role is and how that role relates to these transformational decisions that have to go faster, not slower. >> Well, the biggest part of my role right now, that's touching on this is leading the transformation office that Antonio set up. And that is really focused on leading our transformation to being the Edge to Cloud as a platform company. And so I'm spending a tremendous amount of my time on that transformation. But in addition, IT has moved into my organization, and I have a number of other administrative organizations. And so I see what is needed in terms of simplifying operations, whether it's ITOps or other parts of the organization and how we need to use data and insights. So combining my role now as head of the transformation office and moving this pivot to as a service focused on our own IT transformation, and then looking at how it impacts all the other pieces of our operations has been incredibly valuable. We just launched our data office, the first-ever data office inside HPE which is also part of my organization, all intended to tie these pieces together because as companies continue to grow, develop, and in fact, try to become more agile and act with a greater sense of urgency. It really is that combination of transforming your own IT, understanding what those new services are that are out there that will allow you to do that. And then putting data at the center of everything you do in terms of driving those actionable insights. And so that's where I've been focused, and I expect to spend a lot more of my time over the next year or two. >> I can only imagine, love that mission. Also, just for the folks watching you guys did indicate that. And as Antonio said publicly that everything will be sold as a service by HPE by 2022. Certainly, we'll be tracking that and want to ask more about that later. But you mentioned data, and this is where I think you're starting to see the biggest impact. Data and data silos as the real blocker for the new operating model. And sometimes there's compliance involved, certainly outside the United States it's regulations, privacy, all kinds of checkboxes is on the apps. So if you're an app developer, nevermind a business leader, you're dealing with the role of data, and more data makes machine learning smarter. So we know that. So this is a challenge. Can you share your thoughts on that? Because you want to have a bottoms up organic growth of data availability, but yet manage some of the top-down policies that might be needed in place from a protection whether its privacy or whatever. So it's really balancing that innovation formula of data everywhere, certainly at the edge for processing. This is now changing everything. This is a big deal. Could you share your thoughts on this? >> Yeah, I think there's certainly some challenges around privacy. Although we're seeing efforts made in a lot of different forums to realize or take into recognition what's actually happening in terms of the needs of companies and so forth. Honestly, in the position I'm in, I don't see regulation as being the primary stumbling block at the moment. The primary stumbling block inside companies like HPE is that siloed aspect with which we keep data. And ultimately we have to recognize that data isn't just sort of an asset. It is, in fact, ultimately the key to unlocking the greatest insight inside the company. And it has to be in movement. We need an active data, not just a data lake that everyone else can sort of access, but we need data flows that allow us to drive that cross-silo collaboration, and most importantly, to fuel AI and ML. That's certainly what we're focused on. That's why we launched our data office. And obviously, it ties in incredibly well to the transformation office and then what we're trying to do with our own IT. >> So the role of work is critical right now. The word work now has multiple meanings workforce, people, workplace, offices, now home. Workflows and workloads cloud and supply chain or any kind of value chain. These things are upside down. It's where all the energy is being spent. And so you said earlier, take away that the burden and make it easier for businesses to focus on this. Could you share your observation of things that executives and business leaders or practitioners should pay attention to as they start to reimagine work? 'Cause it's not just the "future of work" and collaboration. That's one thing, but what I just laid out is across the board end to end challenge. What's your observation? >> Well, certainly, you can think about it across the three traditional directions of people, process, and technology. And as you mentioned, look, the people element, especially by virtue of what's happened with COVID-19, is completely changed. And at HPE, we were focused on the workplace experience and in particular thinking about our sites and the like, and we were very quickly transformed into recognizing that the workplace experience now isn't just going to be in the office and candidly may not just be in the home, but it's a more fluid and dynamic workplace experience and how you enable that, create the right amount of productivity, but also the right amount of collaboration and camaraderie, it is critically important. On the process side, the opportunity with ML and AIOps, the ability to use data, and drive those actionable insights is really changing the game around processes. And folks have to rethink their end to end processes. Many of which are manual or people who operate through intuition versus data-driven and actual insight-driven sort of basis. So we're very focused on that piece as well. And I don't think everyone else is seeing the same thing on the technology side, which is as I said, people want to get out of spending time and investing dollars in operations. They now expect that to be happening for them. And what they want is someone who's delivering them an outcome or a solution that they can then drive through their business. And so whether it's the work that Kumar's doing with the element, whether it's the work that we're doing with respect to ours, as a service solution that we're going to be introducing here at Virtual Discover, their workplace, excuse me, their workflow focused right their workload-optimized, and it's less around selling a particular piece of infrastructure. It's now selling a solution that's intended to solve a real customer problem. That's what everyone wants to hear us talk about. And that's obviously where we're putting our focus. >> And that's where everyone's energy is on. And also, there's also the reinvention piece that I'd love to get your personal perspective on this job because of your background, your experience, and your current position. This kind of conversation I was just having with a CEO of a big company we've been talking we were like, "Well the new stuff is either the old stuff "at the same as the old stuff." Or, "It's either a little bit better than the old way," or, "It does something completely different and better "than the old way." And so people are trying to figure out as they bring in this world and these new apps are going to be refactored and modernized that it can't just be the same thing in a new box or a new solution. >> Absolutely. >> It has to be either significantly better, lower-cost, or completely different and completely better. And so, as we are embarking on a first time challenge globally around virtual first or remote first, whatever want to call it, I call it virtual first. You're dealing with policies, legal precedents that aren't their formulation of things have to be taken into account. All of this legacy business model value is going to be reshifted. And that's going to be an opportunity, for someone to build software for HR, for HR virtual, that environment. So all new things will be built around virtual first. As someone has an expert in that area, how do you think about that? What advice would you give folks out there? Whether it's a business or a developer who's going to make, might build the best HR app for virtual companies that no one's ever done before. It's not workday for virtual to users virtual first it's coming. >> No, I agree. Look, I think one of the things that we often see in the technology world is people build technology out. They have a mindset around the technology. They think about what that technology can do, and then they take it to market in a way that's really kind of technology first. And look, having been in a technology company for the last dozen years, I certainly understand the power of technology and the fuel that it provides. But I think what's changing, and I think it happened really when you think about sort of the mobile phone and then the apps and services that came with it is really that customer-first focus and that driving what happens on the technology side, whether it's a virtual HR delivery, or whether it's something happening in the legal space or supply chain or anywhere else. And that's really where we have changed our focus. It's not about being customer friendly, it's about being customer experience-oriented. And that really starts to drill in on what are the solutions, excuse me, what are the problems our customers are trying to solve? How are we going to solve them, and how are we going to do that better than everyone else. And that is a full shift in terms of how we develop our technology, how we go to market with our technology. And it really requires you to have a broader understanding of what your customers are really trying to achieve. Whether that's through an application, whether that's through the infrastructure services it's across the board. It sounds very simple, and on one level it is. But in terms of trying to change an entire organization to become customer experience led is more difficult and more challenging. And like I said, I think many companies are trying to do the same thing right now. And they realize that is a challenge. >> The good news is you have technology scale that's helping get a tailwind on the technology scale side, data, planes, or, however, that's going to evolve is rapidly changing as well. That's an opportunity. And the environment's forcing everyone to have new ways of doing things. So I think if you're going to make a change it a good time now. >> We also have... The thing about HPE is, we have some tremendously deep and rich customer relationships. And there's no substitute for that. And the second thing is, we have a phenomenal partner ecosystem. And our partners are been a key to the success of HPE for a long time. It's not just the ability to service customers, but it's the insight we get about customers do our partner network. And so I think we've got some real advantages there, in terms of driving the right kind of customer experience. It's that deep relationships that we already have, whether it's through Pointnext, which has an unbelievable net promoter score because of the quality of what they do and the deepness of that relationship. And again, the phenomenal partner ecosystem that we have, which just fuels the customer focus of our organization. >> I came up with point out, but also you can also offering HPE has financial services as well. That's now front and center. That's now not just a bolt-on option, it's fundamental now, could you just comment quickly on important to that. >> Oh, it's such a differentiator. It's such a differentiator for us. Clearly, it fuels our as a service and our consumption offerings. But when you get into life cycle management and especially sort of the upcycling capacity of HPFS with two of the world's largest up-cycling facilities, one in Scotland, one here in the US, we're able to provide a set of services to customers that really are unique. And what's great about it is, it's changing the game around sustainability and the circular economy. Most of the equipment we take back and run through our up-cycling service centers, either get refurbished and put back into use or get recycled. I mean, that is what people want to talk about today. Not just, "Hey, what's the newest thing in your technology?" But are you being responsible from a climate perspective? And we can say, absolutely, we are a leader in that space and HPFS is a huge part of that solution. So it continues to be a differentiator for us. And we see the opportunities on the HPFS side only growing. >> And not just for the large enterprise, either for the SMEs, for instance, that are dealing with COVID, they have to make their dollars work for the return on investment, and with the consumption model, which is proven in the cloud model, you get the value faster, you don't want to take on that front end costs, you guys, and that's not just an option, that's part of the value that people need right now. >> It's absolutely part of the value. And it comes up in big ways with respect to a greenlight deal or the light, but it comes up in other ways. We've had companies reach out who needed laptops to service their work from home workers. And HPFS has a inventory of refurbished PCs that they were able to deploy in a very short period of time to a customer. You can imagine the goodwill with that in genders in a situation like this with crisis is tremendous. So we do have a tremendous asset in HPFS. It's not just about financing. It's about the entire array of services that they provide that really sort of sync well with the rest of our business. And I think, again, gives us the ability to deliver a customer experience that is unlike any other company in the market. >> And I'm going to say now go out on a limb and say this, but I think business value right now, post-COVID is a social impact initiative. Business is needed now more than ever to get back to work. It's not just impact investing for societal benefits, although it's a lot to do there, the business issue is impact. So I think that's a very good for you guys to do that, I appreciate that. Okay, closing it out, John, we'll get your final question. I've been asking everyone to finish this sentence. HPE is competitive advantage to our clients is, blank. How would you answer that question? >> I think it's our ability to provide a genuine cloud experience, On-Premise, at the Edge, and a Colo. We really sort of pioneered, I think the concept of Hybrid Cloud. Now, if you want to talk about it in the context of distributed cloud or multi-cloud, I think we're the leader, there, the thought leader there, but we're also aiming to be the execution leader there in delivering those solutions that will drive the next wave of innovation inside HPE and continue to establish us on as the Edge to cloud platform as a service company. I'm so super excited about it, and thanks for the opportunity to talk about it. >> Well, thank you for spending your valuable time. And congratulations on the transformation initiative that you're heading up. And I agree with all the things you said I would add the data piece is going to be a super valuable component. I think you're right on the money on that point. Thanks for your time. John Schultz, Chief Legal and Administrative Officer at HPE, joining me here inside theCUBE Studios, Palo Alto. I'm John, for your host. Thanks for watching. (upbeat music)

>> (vocalizing) >> Narrator: From theCube studios in Palo Alto and Boston, it's theCube. Covering IBM Think, brought to you by IBM. >> Hi everybody, this is Dave Vallante and this is our continuing coverage of Think 2020, the digital event experience. This is the post-thing, the sort of halo effect, the afterthoughts, and joining me is Rob Thomas, he's back. The Senior Vice president of Cloud and Data Platform. Rob, thanks for taking some time to debrief on Think. >> Absolutely Dave, great to be here, good to see you again. >> Yeah, so you have a great event, you guys put it together in record time. I want to talk about sort of your innovation agenda. I mean, you are at the heart of innovation. You're talking cloud, data, AI, really the pillars of innovation, I could probably add in edge to extend the cloud. But I wonder if you could talk about your vision for the innovation agenda and how you're bringing that to customers. I mean, we heard from PayPal, you talked about Royal Bank of Scotland, Credit Mutual, a number of customer examples. How are you bringing innovation forward with the customer? >> I wouldn't describe innovation, maybe I'd give it two different categories. One is, I think the classic term would be consumerization, and you're innovating by making interiorized technology really easy to use. That's why we built out a huge design capability, it's why we've been able to get products like Watson Assistant to get companies live in 24 hours. That's the consumerization aspect, just making enterprise products really easy to use. The second aspect is even harder, which is, how do you tap into an institution like IBM Research, where we're doing fundamental invention. So, one of our now strengths in the last couple of months was around taking technology out of IBM Debater, project Debater, the AI system that could debate humans and then putting that into enterprised products. And, you saw companies like PayPal that are using Watson Assistant and now they have access to that kind of language capability. There's only two aspects here, there's the consumerization and then there's about fundamental technology that really changes how businesses can operate. >> I mean, the point you made about speed and implementation in your key note was critical, I mean really, within 24 hours, very important during this pandemic. Talk about automation, you know, you would think by now right, everything's automation. But, now you're seeing a real boom in automation and it really is driven by AI, all this data, so there's seems to be a next wave, almost a renaissance, if you will, in automation. >> There is and I think automation, when people hear first of the term, it's sometimes a scary term. Because people are like hey, is this going to take my job? Gain a lot of momentum for automation is a difficult, repetitive tasks that nobody really wanted to do in the first place. Whether it's things like data matching, containerizing an application. All these are really hard things and the output's great, but nobody really wants to do that work, they just want the outcome. And, as we've started to demonstrate different use cases for automation that are in that realm, a lot of momentum has taken off, that we're seeing. >> I want to come back to this idea of consumerization and simplification. I mean, when you think about what's been happening over the last several years. And, you and I have talked about this a lot, AI for consumer versus AI for business and enterprise. And really, one of the challenges for the encumbrance, if you will, is to really become data driven, put data at the core and apply machine intelligence to that, just to that data. Now the good news is, they don't have to invent all this stuff, because guys like you are doing that and talk about how you're making that simple. I mean, cloud packs is an example of that, simplification, but talk about how customers are going to be able to tap into AI without having to be AI inventors. >> Well, the classic AI problem actually is a data problem, and the classic data problem is data slide over, which is a company has got a lot of data but it's spread across a hundred or a thousand or tens of thousands different repositories or locations. Our strategy when we say a hybrid cloud is about how do we unify those data storage. So, it's called PaaS, on red hat open shift. We do a lot of things like data virtualization, really high performance. So, we take what is thousands of different data sources and we have that packed like a single fluid item. So then, when you're training models, you can train your models in one place and connect to all your data. That is the big change that's happening and that's how you take something like hybrid cloud, and it actually starts to impact your data architecture. And once you're doing that, then AI becomes a lot easier, because the biggest AI challenge that I described is, where's the data? Is the data in a usable form? >> A lot of times in this industry, you know, we go whale hunting, there are a lot of big companies out there, a lot of times they take priority. You know, at the same time though, a lot of the innovations are coming from companies, you know, we've never even heard of that could be multi-billion dollar companies by the end of the decade. So, how can, you know, small companies and mid-sized companies tap into this trend? Is it just for the big whales or could the small guys participate? >> The thing that's pretty amazing about modern cloud and data technology, I'll call it, is it's accessible to companies of any size. When we talked about, you know, the hundred or so clients that have adopted Watson Assistant since COVID-19 started, many of those are very small institutions with no IT staff or very limited IT staff. Though, we're making this technology very accessible. when you look at something like data, now a small company may not have a hundred different repositories, which is fine, but what they do have is they do want to make better predictions, they do want to automate, they do want to optimize the business processes that they're running in their business. And, the way that we've transformed our model consumption base starting small, it's really making technology available to, you know, from anywhere from the local deli to the Fortune 50 Company. >> So, last question is, What are your big takeaways from Think? I would ask that question normally when we're in a live event. It's a little different with the digital event, but there are still takeaways. What was your reaction and what do to leave people with? >> Even as we get back to doing physical events, which I'm positive will happen at some point. What we learned is there is something great about an immersive digital experience. So, I think the future of events is probably higher than this. Meaning, a big digital experience, to complement the physical experience. That's one big takeaway because the reaction was so positive to the content and how people could access it. Second one is the, all the labs that we did. So, for developers, builders, those were at capacity, meaning we didn't even take any more. So, there's definitively a thirst in the market for developing new applications, developing new data products, developing new security products. That's clear just by the attendance that we saw, that's exciting. Now, I'd say third, that is that AI is now moving into the mainstream, that was clear from the customer examples, whether it was with Tansa or UPS or PayPal that I mentioned before, that was talking with me. AI is becoming accessible to every company, that's pretty exciting. >> Well, the world is hybrid, oh you know the lab, the point you're making about labs is really important. I've talked to a number of individuals saying, "Hey I'm using this time to update my skills. I'm working longer hours, maybe different times of the day, but I'm going to skill up." And you know, the point about AI, 37 years ago, when I started in this business AI was all the buzz and it didn't happen. It's real this time and I'm really excited Rob, that you're at the heart of all this innovation, so really, I appreciate you taking the time. And, best of luck, stay safe, and hopefully we'll see you face to face. >> Offscreen Man: Sure. >> Thanks Dave, same to you and the whole team at theCube, take care. >> Thank you Rob, and thank you for watching everybody, this is Dave Vellante for theCube and our coverage of IBM Think 2020, the digital event experience and the post-event. We'll see you next time. (music)

>>live from Miami, Florida. It's the Q covering. IBM is data in a I forum brought to you by IBM. >>Welcome back to the port of Miami, Everybody. You're watching the Cube, the leader in live tech coverage. We're here covering the IBM data and a I form. Rob Thomas is here. He's the general manager for data in A I and I'd be great to see again. >>Right. Great to see you here in Miami. Beautiful week here on the beach area. It's >>nice. Yeah. This is quite an event. I mean, I had thought it was gonna be, like, roughly 1000 people. It's over. Sold or 17. More than 1700 people here. This is a learning event, right? I mean, people here, they're here to absorb best practice, you know, learn technical hands on presentations. Tell us a little bit more about how this event has evolved. >>It started as a really small training event, like you said, which goes back five years. And what we saw those people, they weren't looking for the normal kind of conference. They wanted to be hands on. They want to build something. They want to come here and leave with something they didn't have when they arrived. So started as a little small builder conference and now somehow continues to grow every year, which were very thankful for. And we continue to kind of expand at sessions. We've had to add hotels this year, so it's really taken off >>you and your title has two of the three superpowers data. And of course, Cloud is the third superpower, which is part of IBMs portfolio. But people want to apply those superpowers, and you use that metaphor in your your keynote today to really transform their business. But you pointed out that only about a eyes only 4 to 10% penetrated within organizations, and you talked about some of the barriers that, but this is a real appetite toe. Learn isn't there. >>There is. Let's go talk about the superpower for a bit. A. I does give employees superpowers because they can do things now. They couldn't do before, but you think about superheroes. They all have an origin story. They always have somewhere where they started and applying a I an organization. It's actually not about doing something completely different. It's about extenuating. What you already d'oh doing something massively better. That's kind of in your DNA already. So we're encouraging all of our clients this week like use the time to understand what you're great at, what your value proposition is. And then how do you use a I to accentuate that? Because your superpower is only gonna last if it's starts with who you are as a company or as a >>person who was your favorite superhero is a kid. Let's see. I was >>kind of into the whole Hall of Justice. Super Superman, that kind of thing. That was probably my cartoon. >>I was a Batman guy. And the reason I love that movie because all the combination of tech, it's kind of reminds me, is what's happening here today. In the marketplace, people are taking data. They're taking a I. They're applying machine intelligence to that data to create new insights, which they couldn't have before. But to your point, there's a There's an issue with the quality of data and and there's a there's a skills gap as well. So let's let's start with the data quality problem described that problem and how are you guys attacking it? >>You're a I is only as good as your data. I'd say that's the fundamental problem and organization we worked with. 80% of the projects get slowed down or they get stopped because the company has a date. A problem. That's why we introduce this idea of the A i ladder, which is all of the steps that a company has to think about for how they get to a level of data maturity that supports a I. So how they collect their data, organize their data, analyze their data and ultimately begin to infuse a I into business processes soap. Every organization needs to climb that ladder, and they're all different spots. So for someone might be, we gotta focus on organization a data catalogue. For others, it might be we got do a better job of data collection data management. That's for every organization to figure out. But you need a methodical approach to how you attack the data problem. >>So I wanna ask you about the Aye aye ladder so you could have these verbs, the verbs overlay on building blocks. I went back to some of my notes in the original Ai ai ladder conversation that you introduced a while back. It was data and information architecture at the at the base and then building on that analytics machine learning. Aye, aye, aye. And then now you've added the verbs, collect, organized, analyze and infused. Should we think of this as a maturity model or building blocks and verbs that you can apply depending on where you are in that maturity model, >>I would think of it as building blocks and the methodology, which is you got to decide. Do wish we focus on our data collection and doing that right? Is that our weakness or is a data organization or is it the sexy stuff? The Aye. Aye. The data science stuff. We just This is just a tool to help organizations organize themselves on what's important. I asked every company I visit. Do you have a date? A strategy? You wouldn't believe the looks you get when you ask that question, you get either. Well, she's got one. He's got one. So we got seven or you get No, we've never had one. Or Hey, we just hired a CDO. So we hope to have one. But we use the eye ladder just as a tool to encourage companies to think about your data strategy >>should do you think in the context I want follow up on that data strategy because you see a lot of tactical data strategies? Well, we use Data Thio for this initiative of that initiative. Maybe in sales or marketing, or maybe in R and D. Increasingly, our organization's developing. And should they develop a holistic data strategy, or should they trying to just get kind of quick wins? What are you seeing in the marketplace? >>It depends on where you are in your maturity cycle. I do think it behooves every company to say We understand where we are and we understand where we want to go. That could be the high level data strategy. What are our focus and priorities gonna be? Once you understand focus and priorities, the best way to get things into production is through a bunch of small experiments to your point. So I don't think it's an either or, but I think it's really valuable tohave an overarching data strategy, and I recommended companies think about a hub and spokes model for this. Have a centralized chief date officer, but your business units also need a cheap date officer. So strategy and one place execution in another. There's a best practice to going about this >>the next you ask the question. What is a I? You get that question a lot, and you said it's about predicting, automating and optimizing. Can we unpack that a little bit? What's behind those three items? >>People? People overreact a hype on topics like II. And they think, Well, I'm not ready for robots or I'm not ready for self driving Vehicles like those Mayor may not happen. Don't know. But a eyes. Let's think more basic it's about can we make better predictions of the business? Every company wants to see a future. They want the proverbial crystal ball. A. I helped you make better predictions. If you have the data to do that, it helps you automate tasks, automate the things that you don't want to do. There's a lot of work that has to happen every day that nobody really wants to do you software to automate that there's about optimization. How do you optimize processes to drive greater productivity? So this is not black magic. This is not some far off thing. We're talking about basics better predictions, better automation, better optimization. >>Now interestingly, use the term black magic because because a lot of a I is black box and IBM is always made a point of we're trying to make a I transparent. You talk a lot about taking the bias out, or at least understanding when bias makes sense. When it doesn't make sense, Talk about the black box problem and how you're addressing. >>That starts with one simple idea. A eyes, not magic. I say that over and over again. This is just computer science. Then you have to look at what are the components inside the proverbial black box. With Watson, we have a few things. We've got tools for clients that want to build their own. Aye, aye, to think of it as a tool box you can choose. Do you want a hammer and you want a screwdriver? You wanna nail you go build your own, aye, aye. Using Watson. We also have applications, so it's basically an end user application that puts a I into practice things like Watson assistant to virtually no create a virtual agent for customer service or Watson Discovery or things like open pages with Watson for governance, risk and compliance. So, aye, aye, for Watson is about tools. You want to build your own applications if you want to consume an application, but we've also got in bed today. I capability so you can pick up Watson and put it inside of any software product in the >>world. He also mentioned that Watson was built with a lot of of of, of open source components, which a lot of people might not know. What's behind Watson. >>85% of the work that happens and Watson today is open source. Most people don't know that it's Python. It's our it's deploying into tensorflow. What we've done, where we focused our efforts, is how do you make a I easier to use? So we've introduced Auto Way. I had to watch the studio, So if you're building models and python, you can use auto. I tow automate things like feature engineering algorithm, selection, the kind of thing that's hard for a lot of data scientists. So we're not trying to create our own language. We're using open source, but then we make that better so that a data scientist could do their job better >>so again come back to a adoption. We talked about three things. Quality, trust and skills. We talked about the data quality piece we talked about the black box, you know, challenge. It's not about skills you mention. There's a 250,000 person Gap data science skills. How is IBM approaching how our customers and IBM approaching closing that gap? >>So think of that. But this in basic economic terms. So we have a supply demand mismatch. Massive demand for data scientists, not enough supply. The way that we address that is twofold. One is we've created a team called Data Science Elite. They've done a lot of work for the clients that were on stage with me, who helped a client get to their first big win with a I. It's that simple. We go in for 4 to 6 weeks. It's an elite team. It's not a long project we're gonna get you do for your success. Second piece is the other way to solve demand and supply mismatch is through automation. So I talked about auto. Aye, aye. But we also do things like using a eye for building data catalogs, metadata creation data matching so making that data prep process automated through A. I can also help that supply demand. Miss Max. The way that you solve this is we put skills on the field, help clients, and we do a lot of automation in software. That's how we can help clients navigate this. So the >>data science elite team. I love that concept because way first picked up on a couple of years ago. At least it's one of the best freebies in the business. But of course you're doing it with the customers that you want to have deeper relationships with, and I'm sure it leads toe follow on business. What are some of the things that you're most proud of from the data science elite team that you might be able to share with us? >>The clients stories are amazing. I talked in the keynote about origin stories, Roll Bank of Scotland, automating 40% of their customer service. Now customer SATs going up 20% because they put their customer service reps on those hardest problems. That's data science, a lead helping them get to a first success. Now they scale it out at Wonderman Thompson on stage, part of big W P p big advertising agency. They're using a I to comb through customer records they're using auto Way I. That's the data science elite team that went in for literally four weeks and gave them the confidence that they could then do this on their own. Once we left, we got countless examples where this team has gone in for very short periods of time. And clients don't talk about this because they have to talk about it cause they're like, we can't believe what this team did. So we're really excited by the >>interesting thing about the RVs example to me, Rob was that you basically applied a I to remove a lot of these mundane tasks that weren't really driving value for the organization. And an R B s was able to shift the skill sets. It's a more strategic areas. We always talk about that, but But I love the example C. Can you talk a little bit more about really, where, where that ship was, What what did they will go from and what did they apply to and how it impacted their businesses? A improvement? I think it was 20% improvement in NPS but >>realizes the inquiry's they had coming in were two categories. There were ones that were really easy. There were when they were really hard and they were spreading those equally among their employees. So what you get is a lot of unhappy customers. And then once they said, we can automate all the easy stuff, we can put all of our people in the hardest things customer sat shot through the roof. Now what is a virtual agent do? Let's decompose that a bit. We have a thing called intent classifications as part of Watson assistant, which is, it's a model that understands customer a tent, and it's trained based on the data from Royal Bank of Scotland. So this model, after 30 days is not very good. After 90 days, it's really good. After 180 days, it's excellent, because at the core of this is we understand the intent of customers engaging with them. We use natural language processing. It really becomes a virtual agent that's done all in software, and you can only do that with things like a I. >>And what is the role of the human element in that? How does it interact with that virtual agent. Is it a Is it sort of unattended agent or is it unattended? What is that like? >>So it's two pieces. So for the easiest stuff no humans needed, we just go do that in software for the harder stuff. We've now given the RVs, customer service agents, superpowers because they've got Watson assistant at their fingertips. The hardest thing for a customer service agent is only finding the right data to solve a problem. Watson Discovery is embedded and Watson assistant so they can basically comb through all the data in the bank to answer a question. So we're giving their employees superpowers. So on one hand, it's augmenting the humans. In another case, we're just automating the stuff the humans don't want to do in the first place. >>I'm gonna shift gears a little bit. Talk about, uh, red hat in open shift. Obviously huge acquisition last year. $34 billion Next chapter, kind of in IBM strategy. A couple of things you're doing with open shift. Watson is now available on open shifts. So that means you're bringing Watson to the data. I want to talk about that and then cloudpack for data also on open shifts. So what has that Red had acquisition done for? You obviously know a lot about M and A but now you're in the position of you've got to take advantage of that. And you are taking advantage of this. So give us an update on what you're doing there. >>So look at the cloud market for a moment. You've got around $600 million of opportunity of traditional I t. On premise, you got another 600 billion. That's public clouds, dedicated clouds. And you got about 400 billion. That's private cloud. So the cloud market is fragmented between public, private and traditional. I t. The opportunity we saw was, if we can help clients integrate across all of those clouds, that's a great opportunity for us. What red at open shift is It's a liberator. It says right. Your application once deployed them anywhere because you build them on red hot, open shift. Now we've brought cloudpack for data. Our data platform on the red hot open shift certified on that Watson now runs on red had open shift. What that means is you could have the best data platform. The best Aye, Aye. And you can run it on Google. Eight of us, Azure, Your own private cloud. You get the best, Aye. Aye. With Watson from IBM and run it in any of those places. So the >>reason why that's so powerful because you're able to bring those capabilities to the data without having to move the date around It was Jennifer showed an example or no, maybe was tail >>whenever he was showing Burt analyzing the data. >>And so the beauty of that is I don't have to move any any data, talk about the importance of not having Thio move that data. And I want I want to understand what the client prerequisite is. They really take advantage of that. This one >>of the greatest inventions out of IBM research in the last 10 years, that hasn't gotten a lot attention, which is data virtualization. Data federation. Traditional federation's been around forever. The issue is it doesn't perform our data virtualization performance 500% faster than anything else in the market. So what Jennifer showed that demo was I'm training a model, and I'm gonna virtualized a data set from Red shift on AWS and on premise repositories a my sequel database. We don't have to move the data. We just virtualized those data sets into cloudpack for data and then we can train the model in one place like this is actually breaking down data silos that exist in every organization. And it's really unique. >>It was a very cool demo because what she did is she was pulling data from different data stores doing joins. It was a health care application, really trying to understand where the bias was peeling the onion, right? You know, it is it is bias, sometimes biases. Okay, you just got to know whether or not it's actionable. And so that was that was very cool without having to move any of the data. What is the prerequisite for clients? What do they have to do to take advantage of this? >>Start using cloudpack for data. We've got something on the Web called cloudpack experiences. Anybody can go try this in less than two minutes. I just say go try it. Because cloudpack for data will just insert right onto any public cloud you're running or in your private cloud environment. You just point to the sources and it will instantly begin to start to create what we call scheme a folding. So a skiing version of the schema from your source writing compact for data. This is like instant access to your data. >>It sounds like magic. OK, last question. One of the big takeaways You want people to leave this event with? >>We are trying to inspire clients to give a I shot. Adoption is 4 to 10% for what is the largest economic opportunity we will ever see in our lives. That's not an acceptable rate of adoption. So we're encouraging everybody Go try things. Don't do one, eh? I experiment. Do Ah, 100. Aye, aye. Experiments in the next year. If you do, 150 of them probably won't work. This is where you have to change the cultural idea. Ask that comes into it, be prepared that half of them are gonna work. But then for the 52 that do work, then you double down. Then you triple down. Everybody will be successful. They I if they had this iterative mindset >>and with cloud it's very inexpensive to actually do those experiments. Rob Thomas. Thanks so much for coming on. The Cuban great to see you. Great to see you. All right, Keep right, everybody. We'll be back with our next guest. Right after this short break, we'll hear from Miami at the IBM A I A data form right back.

>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>Welcome everybody to the port of Miami. My name is Dave Vellante and you're watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise and we're here at the IBM data and AI form. The hashtag is data AI forum. This is IBM's. It's formerly known as the, uh, IBM analytics university. It's a combination of learning peer network and really the focus is on AI and data. And there are about 1700 people here up from, Oh, about half of that last year, uh, when it was the IBM, uh, analytics university, about 600 customers, a few hundred partners. There's press here, there's, there's analysts, and of course the cube is covering this event. We'll be here for one day, 128 hands-on sessions or ER or sessions, 35 hands on labs. As I say, a lot of learning, a lot of technical discussions, a lot of best practices. >>What's happening here. For decades, our industry has marched to the cadence of Moore's law. The idea that you could double the processor performance every 18 months, doubling the number of transistors, you know, within, uh, the footprint that's no longer what's driving innovation in the it and technology industry today. It's a combination of data with machine intelligence applied to that data and cloud. So data we've been collecting data, we've always talked about all this data that we've collected and over the past 10 years with the advent of lower costs, warehousing technologies in file stores like Hadoop, um, with activity going on at the edge with new databases and lower cost data stores that can handle unstructured data as well as structured data. We've amassed this huge amount of, of data that's growing at a, at a nonlinear rate. It's, you know, this, the curve is steepening is exponential. >>So there's all this data and then applying machine intelligence or artificial intelligence with machine learning to that data is the sort of blending of a new cocktail. And then the third piece of that third leg of that stool is the cloud. Why is the cloud important? Well, it's important for several reasons. One is that's where a lot of the data lives too. It's where agility lives. So cloud, cloud, native of dev ops, and being able to spin up infrastructure as code really started in the cloud and it's sort of seeping to to on prem, slowly and hybrid and multi-cloud, ACC architectures. But cloud gives you not only that data access, not only the agility, but also scale, global scale. So you can test things out very cheaply. You can experiment very cheaply with cloud and data and AI. And then once your POC is set and you know it's going to give you business value and the business outcomes you want, you can then scale it globally. >>And that's really what what cloud brings. So this forum here today where the big keynotes, uh, Rob Thomas kicked it off. He uh, uh, actually take that back. A gentleman named Ray Zahab, he's an adventure and ultra marathon or kicked it off. This Jude one time ran 4,500 miles in 111 days with two ultra marathon or colleagues. Um, they had no days off. They traveled through six countries, they traversed Africa, the continent, and he took two showers in a 111 days. And his whole mission is really talking about the power of human beings, uh, and, and the will of humans to really rise above any challenge would with no limits. So that was the sort of theme that, that was set for. This, the, the tone that was set for this conference that Rob Thomas came in and invoked the metaphor of superheroes and superpowers of course, AI and data being two of those three superpowers that I talked about in addition to cloud. >>So Rob talked about, uh, eliminating the good to find the great, he talked about some of the experiences with Disney's ward. Uh, ward Kimball and Stanley, uh, ward Kimball went to, uh, uh, Walt Disney with this amazing animation. And Walter said, I love it. It was so funny. It was so beautiful, was so amazing. Your work 283 days on this. I'm cutting it out. So Rob talked about cutting out the good to find, uh, the great, um, also talking about AI is penetrated only about four to 10% within organizations. Why is that? Why is it so low? He said there are three things that are blockers. They're there. One is data and he specifically is referring to data quality. The second is trust and the third is skillsets. So he then talked about, you know, of course dovetailed a bunch of IBM products and capabilities, uh, into, you know, those, those blockers, those challenges. >>He talked about two in particular, IBM cloud pack for data, which is this way to sort of virtualize data across different clouds and on prem and hybrid and and basically being able to pull different data stores in, virtualize it, combine join data and be able to act on it and apply a machine learning and AI to it. And then auto AI a way to basically machine intelligence for artificial intelligence. In other words, AI for AI. What's an example? How do I choose the right algorithm and that's the best fit for the use case that I'm using. Let machines do that. They've got experience and they can have models that are trained to actually get the best fit. So we talked about that, talked about a customer, a panel, a Miami Dade County, a Wunderman Thompson, and the standard bank of South Africa. These are incumbents that are using a machine intelligence and AI to actually try to super supercharge their business. We heard a use case with the Royal bank of Scotland, uh, basically applying AI and driving their net promoter score. So we'll talk some more about that. Um, and we're going to be here all day today, uh, interviewing executives, uh, from, uh, from IBM, talking about, you know, what customers are doing with a, uh, getting the feedback from the analysts. So this is what we do. Keep it right there, buddy. We're in Miami all day long. This is Dave Olanta. You're watching the cube. We'll be right back right after this short break..

>>live >>from Denver, Colorado. It's the Q covering com vault Go 2019. Brought to you by combo. >>Hey, welcome to the Cube. Lisa Martin in Colorado for CONMEBOL Go 19. Statement. A man is with me this week, and we are pleased to welcome one of combos, longtime customers from the University of Leicester. We have Mark Penny, the systems specialist in infrastructure. Mark. Welcome to the Cube. >>Hi. It's good to be here. >>So you have been a convo customer at the UNI for nearly 10 years now, just giving folks an idea of about the union got 51 different academic departments about five research institutes. Cool research going on, by the way and between staff and students. About 20,000 folks, I'm sure all bringing multiple devices onto the campus. So talk to us about you came on board in 20 ton. It's hard to believe that was almost 10 years ago and said, All right, guys, we really got to get a strategy around back up, talk to us about way back then what? You guys were doing what you saw as an opportunity. What you're doing with combo today, a >>time and the There's a wide range of backup for us. There was no really assurance that we were getting back up. So we had a bit of convert seven that was backing up the Windows infrastructure. There was tyranny storage manager backing up a lot of Linux. And there was Amanda and open source thing. And then there was a LL sorts of scripts and things. So, for instance, of'em where backups were done by creating an array snapshot with the script, then mounting that script into that snapshot into another server backing up the server with calm bolt on the restore process is an absolute takes here. It was very, very difficult, long winded, required a lot of time on the checks. For this, it really was quite quite difficult to run it. Use a lot of stuff. Time we were, as far as the corporate side was concerned it exclusively on tape resource manager, we're using disc. Amanda was again for tape in a different, completely isolated system. Coupled with this, there had been a lack of investment in the data centers themselves, so the network hadn't really got a lot of throughput. This men that way were using data private backup networks in order to keep back up data off the production networks because there was really challenges over bandwidth contention backups on. So consider it over around and so on. If you got a back up coming into the working day defect student So Way started with a blank sheet of paper in many respects on went out to see what was available on Dhe. There was the usual ones it with the net back up, typically obviously again on convert Arc Serve has. But what was really interesting was deed Implication was starting to come in, But at the time, convo tonight just be released, and it had an absolutely killer feature for us, which was client side duplication. This men that we could now get rid of most of this private backup network that was making a lot of complex ISI. So it also did backup disk on back up to tape. So at that point, way went in with six Media agents. Way had a few 100 terabytes of disk storage. The strategy was to keep 28 days on disk and then the long term retention on tape into a tape library. WeII kept back through it about 2013 then took the decision. Disc was working, so let's just do disco only on save a whole load of effort. In even with a take life, you've got to refresh the tapes and things. So give it all on disk with D Duplication way, basically getting a 1 to 1. So if we had take my current figures about 1.5 petabytes of front side protected data, we've got about 1.5 petabytes in the back up system, which, because of all the synthetic fools and everything, we've got 12 months retention. We've got 28 days retention. It works really, really well in that and that that relationship, almost 1 to 1 with what's in the back up with all the attention with plants like data, has been fairly consistent since we went all disc >>mark. I wonder if you'd actually step back a second and talks about the role in importance of data in your organization because way went through a lot of the bits and bytes in that is there. But as a research organization, you know, I expect that data is, you know, quite a strategic component of the data >>forms your intellectual property. It's what is caught your research. It's the output of your investigations. So where were doing Earth Operational science. So we get data from satellites and that is then brought down roars time, little files. They then get a data set, which will consist of multiple packages of these, these vials and maybe even different measurements from different satellites that then combined and could be used to model scenarios climate change, temperature or pollution. All these types of things coming in. It's how you then take that raw data work with it. In our case, we use a lot of HPC haIf of computing to manipulate that data. And a lot of it is how smart researchers are in getting their code getting the maximum out of that data on. Then the output of that becomes a paper project on dhe finalized final set of of date, which is the results, which all goes with paper. We've also done the a lot of genetics and things like that because the DNA fingerprinting with Alec Jeffrey on what was very interesting with that one is how it was those techniques which then identified the bones that were dug up under the car park in Leicester, which is Richard >>Wright documentary. >>Yeah, on that really was quite exciting. The way that well do you really was quite. It's quite fitting, really, techniques that the university has discovered, which were then instrumental in identifying that. >>What? One of the interesting things I found in this part of the market is used to talk about just protecting my data. Yeah, a lot of times now it's about howto. Why leverage my data even Maur. How do I share my data? How do I extract more value out of the data in the 10 years you've been working with calm Boulder? Are you seeing that journey? Is that yes, the organization's going down. >>There's almost there's actually two conflicting things here because researchers love to share their data. But some of the data sets is so big that can be quite challenging. Some of the data sets. We take other people's Day to bring it in, combining with our own to do our own modeling. Then that goes out to provide some more for somebody else on. There's also issues about where data could exist, so there's a lot of very strict controls about the N. H s data. So health data, which so n hs England that can't then go out to Scotland on Booth. Sometimes the regulatory compliance almost gets sidelines with the excitement about research on way have quite a dichotomy of making sure that where we know about the data, that the appropriate controls are there and we understand it on Hopefully, people just don't go on, put it somewhere. It's not because some of the data sets for medical research, given the data which has got personal, identifiable information in it, that then has to be stripped out. So you've got an anonymous data set which they can then work with it Z assuring that the right data used the right information to remove so that you don't inadvertently go and then expose stuff s. So it's not just pure research on it going in this silo and in this silo it's actually ensuring that you've got the right bits in the right place, and it's being handled correctly >>to talk to us about has you know, as you pointed out, this massive growth and data volumes from a university perspective, health data perspective research perspective, the files are getting bigger and bigger In the time that you've started this foundation with combo in the last 9 10 years. Tremendous changes not just and data, but talking about complaints you've now got GDP are to deal with. Give us a perspective and snapshot of your of your con vault implementation and how you've evolved that as all the data changes, compliance changes and converts, technology has evolved. So if you take >>where we started off, we had a few 100 petabytes of disk. It's just before we migrated. Thio on Premise three Cloud Libraries That point. I think I got 2.1 petabytes of backup. Storage on the volume of data is exponentially growing covers the resolution of the instruments increases, so you can certainly have a four fold growth data that some of those are quite interesting things. They when I first joined the great excitement with a project which has just noticed Betty Colombo, which is the Mercury a year for in space agency to Demeter Mercury and they wanted 50 terabytes and way at that time, that was actually quite a big number way. We're thinking, well, we make the split. What? We need to be careful. Yes. Okay. 50 terrorizes that over the life of project. And now that's probably just to get us going. Not much actually happened with it. And then storage system changed and they still had their 50 terabytes with almost nothing in it way then understood that the spacecraft being launched and that once it had been launched, which was earlier this year, it was going to take a couple of years before the first data came back. Because it has to go to Venus. It has to go around Venus in the wrong direction, against gravity to slow it down. Then it goes to Mercury and the rial bolt data then starts coming back in. You'd have thought going to Mercury was dead easy. You just go boom straight in. But actually, if you did that because of gravity of the sun, it would just go in. You'd never stop. Just go straight into the sun. You lose your spacecraft. >>Nobody wants >>another. Eggs are really interesting. Is artfully Have you heard of the guy? A satellite? >>Yes. >>This is the one which is mapping a 1,000,000,000 stars in the Milky Way. It's now gone past its primary mission, and it's got most of that data. Huge data sets on DDE That data, there's, ah, it's already being worked on, but they are the university Thio task, packaging it and cleansing it. We're going to get a set of that data we're going to host. We're currently hosting a national HPC facility, which is for space research that's being replaced with an even bigger, more powerful one. Little probably fill one of our data centers completely. It's about 40 racks worth, and that's just to process that data because there's so much information that's come from it. And it's It's the resolution. It's the speed with which it can be computed on holding so much in memory. I mean, if you take across our current HPC systems, we've got 100 terabytes of memory across two systems, and those numbers were just unthinkable even 10 years ago, a terrible of memory. >>So Mark Lease and I would like to keep you here all way to talk about space, Mark todo of our favorite topics. But before we get towards the end, but a lot of changes, that combo, it's the whole new executive team they bought Hedvig. They land lost this metallic dot io. They've got new things. It's a longtime customer. What your viewpoint on com bold today and what what you've been seeing quite interesting to >>see how convoy has evolved on dhe. These change, which should have happened between 10 and 11 when they took the decision on the next generation platform that it would be this by industry. Sand is quite an aggressive pace of service packs, which are then come out onto this schedule. And to be fair, that schedule is being stuck to waken plan ahead. We know what's happening on Dhe. It's interesting that they're both patches and the new features and stuff, and it's really great to have that line to work, too. Now, Andi way with platform now supports natively stone Much stuff. And this was actually one of the decisions which took us around using our own on Prem Estimate Cloud Library. We were using as you to put a tear on data off site on with All is working Great. That can we do s3 on friend on. It's supported by convoy is just a cloud library. Now, When we first started that didn't exist. Way took the decision. It will proof of concept and so on, and it all worked, and we then got high for scale as well. It's interesting to see how convoy has gone down into the appliance 11 to, because people want to have to just have a box unpack it. Implicated. If you haven't got a technical team or strong yo skills in those area, why worry about putting your own system together? Haifa scale give you back up in a vault on the partnerships with were in HP customer So way we're using Apollo's RS in storage. Andi Yeah, the Apollo is actually the platform. If we bought Heifer Scale, it would have gone on an HP Apollo as well, because of the way with agreements, we've got invited. Actually, it's quite interesting how they've gone from software. Hardware is now come in, and it's evolving into this platform with Hedvig. I mean, there was a convoy object store buried in it, but it was very discreet. No one really knew about it. You occasionally could see a term on it would appear, but it it wasn't something which they published their butt object store with the increasing data volumes. Object Store is the only way to store. There's these volumes of data in a resilient and durable way. Eso Hedvig buying that and integrating in providing a really interesting way forward. And yet, for my perspective, I'm using three. So if we had gone down the Hedvig route from my perspective, what I would like to see is I have a story policy. I click on going to point it to s three, and it goes out it provision. The bucket does the whole lot in one a couple of clicks and that's it. Job done. I don't need to go out, create the use of create the bucket, and then get one out of every little written piece in there. And it's that tight integration, which is where I see benefits coming in you. It's giving value to the platform and giving the customer the assurance that you've configured correctly because the process is an automated in convoy has ensured that every step of the way the right decisions being made on that. Yet with metallic, that's everything is about it's actually tried and tested products with a very, very smart work for a process put round to ensure that the decisions you make. You don't need to be a convoy expert to get the outcome and get the backups. >>Excellent. Well, Mark, thank you for joining Student on the Cape Talking about tthe e evolution that the University of Leicester has gone through and your thoughts on com bolts evolution in parallel. We appreciate your time first to Minutemen. I'm Lisa Martin. You're watching the cue from combo go 19.

>> Live from Las Vegas, it's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. >> Hey welcome back everyone, you're here live in Las Vegas for theCUBE, for Informatica World 2019. I'm John Furrier, co-host of theCUBE. We've got two great guests here from Snowflake. We've got Tarik Dwiek who's the Director of Technology Alliances at Snowflake, and Rik Tamm-Daniels, Vice President of Strategic Ecosystems and Technology at Informatica. Welcome back to theCUBE, good to see you guys. >> Good to see you as well. >> Thanks for coming on Snowflake. Congratulations, you guys are doing really well. >> Thank you. >> Big growth, new CEO, Frank Slootman, Informatica, The Data, Zar, Neutral Third Party, Switzerland, cloud, you've got Switzerland, what's the relationship, explain. >> Well, I think you know, it's funny that comment comes up a fair amount and yeah, I look at this way. It's not so much that you know, with Switzerland what we're focused on though is where customers are choosing to go in their journey, we want to provide them the best experience possible, right. So we end up going very deep in our strategic ecosystems, and Snowflakes is one of those partners that we've seen tremendous growth with, and customers are adopting, So, very excited about the partnership. >> How about your relationship with Informatica, Why are you here? What's the story? >> Yeah definitely, so at Snowflake, we put customers first, right? And as Rick mentioned, it's all about having a diverse ecosystem in the enterprise. Informatica is a leader. When you look at where customers are going with data, right? Obviously data integration is key. Data quality is key, data governance. All the areas that Informatica has been the best to breed in, it just makes sense for continued to make traction in these enterprise customers. >> Take a bit to explain the business model of Snowflake, what you guys do, quick one minute. >> Sure, so Snowflake's a data warehouse solution built from the ground up for the cloud. Why the distinction is important is because we're the only data warehouse born in the cloud. If you look at how the other solutions are doing it today, they're taking an architecture, an architecture created a decade ago for an on-premise world and they're just shifting into cloud. And the challenge that you have there is that you can't take full advantage of things like instant and infinite resources, both compute and storage, right? Independent scaling of computing storage. Elasticity right, the ability to scale up and down and out with a click of a button. And then even being able to support massive incurrence. Things like loading data at the same time that you're querying data. This is what Snowflake was built for. >> How about datasets from other people. That's one of the benefits of having data in the cloud. >> Correct, so our architecture is key. That's the key to our business and our product and what we've done is we separated compute from storage and we become a centralized database. And what we found by creating additional views, you can actually share your data with yourself and you can share with other customers. We've created this concept of data sharing. Data sharing has been around for decades, but it's been very painful. What we've done is created an online performant, secure way for customers to share the data. >> Rik this really highlights the value proposition for Informatica. I always say, you know, data is always, beauty of the data is in the eye of the beholder. Depending on where you're sitting in from. You could be on-premises, you have legacy, you could be born in the cloud and taking advantage of all that cloud stuff. Graham Thompson was on earlier he said, "Hey if you've got data in the cloud "why move it on premise?" So you know, there should be a choice of what's best. And that's what you guys come in. What specifically are you guys tying together with data warehouse in the cloud and and maybe a customer may want to choose to have for compliance reasons, or a viariety of other reasons on prem or another location. >> I think one of the big things about cloud data warehouses in particular, it's not all things being equal at the on-premise world, right? The level of agility you get with the Snowflake where it's infinite scale out, up in a few minutes. That empowers so much transformation in the organization. That's why it's so compelling, and so many folks are adopting it. And so what we're doing is we're helping customers on that journey though. Because they've got a very complex data environment and they got to first of all understand how's this all put together to be able to start modernizing moving to the cloud. >> I'm sorry if I asked the question where should a customer store their data; on the cloud or on-premise. I know where you'll come in on that. It's cloud all the way, because that's what you do. But this is something that architects in the enterprise have been dealing with because they do have legacy stuff. So and we've seen with the SAS business models, data has been really key for their success because it gives them risk-taking or, actually risk taking meaning they can do things, maybe testing to whatever. Test certain features on certain users. Basically use the data basically to create value. And then the upside of taking that risk is reward. You have more revenue, hockey stick growth and the numbers are pretty clear. Enterprises want that. >> They do. >> But they're not really set up for it. How do they get there? >> The best part with a SAS model is customers can de-risk by putting some of their data, for instance Snowflake, right? We work across AWS and Azure. So customers that maybe aren't all in yet on either cloud provider can start using Snowflake and put data in Snowflake and test it out. Test out the performance and the security of cloud. And if for whatever reason it doesn't work out they haven't risked very much if anything. And if it does work out then they've got a great proving ground for that. So the SAS opens up a lot of possibilities for enterprise customers. >> I brought this up with Graeme Connelly. You know, he's from Scotland so I understand his perspective. I'm from Silicon Valley so I took my perspective. I said you know, when I hear regulation I see you know, anti innovation, right? Like when I hear governments coming involved putting you know, regulation on things. We're seeing a very active regulatory environment on tech companies around data. GDPR one-year anniversary. This is a real issue. How do you turn that regulatory constraints around data, because what it means is more complexity around how to deal with the data. How do you turn that into an advantage. Obviously software abstraction certainly helps in tech, but customers are trying to move move faster with cloud. They can do that for all those reasons talked earlier. But now you got complexity around regulation. >> I think first off from a from a data warehouse perspective we were built with security and compliance in mind from day one, right? So you build in things like encryption, always-on encryption. You build things like role based access controls. Things like key management, right? And then when you think of Informatica within the data pipeline getting data from sources in and out of Snowflake, then you build additional data quality, data governance tools on top of that. Things like data catalog, right? Where you can, now just go discover what data you have out there, what data are you moving into the cloud, and what is the lineage of that data. >> Talk about this migration and movement because that becomes, people are generally skeptical when they hear migration like, oh my god migration. If they know it's going to cost some money or potentially technical risk. What's, how do you guys handle the migration in a way that's risk-free. >> I'll take that one. I'd say one of the things that we really put in front of all of our migration approaches for customers is the enterprise data catalog. And using the machine learning capabilities in the catalog to take what is a very complex landscape and make it very understandable accessible to the business. But then also understand how it's all put together. Where data's coming from, where it's going, who's consuming it. And once you have that view and that clarity of how things are put together it actually means you can take a use case based approach to adoption of the cloud and moving data. So you're actually realizing business value incrementally as you're moving. Which i think is really key right? if you do these massive multi-year projects and it takes a year to get any results it's not going to fly anymore, right? This is a much more agile world and so we're really empowering of that with the intelligence around data. >> Digital transformation has got three kind of categories we find when we poll people and do the research. You got the early adopters who have a full team they're cloud native, their jammin and their DevOps rockstars. They're kicking ass taking names. Then on the other end of spectrum you got you know, fear, oh my god, like I don't really have the talent. I'm going to do some, study it, spec it out, we got to figure it out. then you have people who are kind of like, you know, the fast followers, influenced kind of like focused. They tend to break down in the middle of projects. This seems to be the pattern. They get going and they get stuck in the mud. This is a real issue around culture and people. So I got to ask you, you know, a lot of these challenges around people and culture is huge skills gap. What is the biggest hiring skills gap that's needed to be filled so that people can be successful whether they're got a really rockstar team or smart team that just got to re-skill up. Or how do you take a project that's stuck in the mud and reboot it? These are challenges. >> I think when the nice things about Informatica is that you know, there's 100,000 folks out there who are familiar with Informatica's approach of implementations. So, by, you know, us bringing our technologies and embracing these journeys we're actually empowering customers to not have to get coders and data scientists. They're using some of those same data engineers but now they're bringing data to the cloud. >> And I think along the same lines we think of practitioners usually right? I need data scientists, I need more data engineers. I think a valuable asset that's that's becoming more clear now, is to have a new breed of data analyst, right? That understand how to put AI and machine learning together. How to start to grab all of the data that's out there for customers, right? Structured data, semi-structured data and make sure that they've got a single strategy along how to become data-driven. >> Give an example of some customers that you guys are working together with using Snowflake and Informatica. What are they, what are they doing? What's some of the use cases? What's some of the applications? >> Yeah so I think one of the biggest use cases is a data warehouse modernization, right? So you have the existing on-premise data warehouses. And I always like when I talk to customers think about, well realistically when you have a new use case on your on-premise warehouse. How long is it going to take you to actually see your first piece of data? I don't know a lot of people have extra capacity that's kind of hanging around in their warehouse right? We think about they have to make business cases, they have to get new Hardware, new licenses. It could take six months to see their first piece of data. So, you know I think it's a tremendous accelerator for them to go to the cloud. >> So the main thing there's agility. >> Yes, absolutely. >> Fast time to value. How's business with Snowflake? What's going on with you guys? What other use case you seeing besides the data warehouse. Modern data warehouse. >> Sure John, I can start with business in general. It's very exciting times at Snowflake right now. Late last year we got a funding round of $450 million for growth funding. Brings our total funding to just over $920 million. Our valuation doubled to 3.9 billion. That puts us in the top 25 highest valued private U.S. tech firms. Like I mentioned before we tripled the number of employees to over a thousand, across nine countries globally. We're going to expand to 20 or more in the next 12 months. And then in terms of my favorite part-- >> What's been the traction of that? Why this success? What's been the ah ha moment for customers with Snowflake? >> Yeah I think about what customers try and do in their data journey, there are probably three key things. Number one, they want to get access to all their data, right? And they want to do that in a very fast and economic way. They want to be able to get all the different variety of data that's out there. All the modern data types, right? Both the structured data, right? Their ERP is CRM systems, things about customers and product, and sales transactions, and then all this modern data, from web and social, from behavior data, from machine generate data in IOT. But they want to put all together. They don't want to have different, disparate systems to go and process this and try to bring back together today. That's been the challenge, is the complexity and the cost. And what we've done is start to remove those barriers. >> You know, I love the term now because I've hated it when it came out. Data Lake, during the Hadoop days we heard Data Lake. And then it turned into a data swamp. You start to see that get fixed a little bit. Because what people are afraid of is they're afraid of throwing all those data into a data swamp. They really want to get value out of it. This has been a hard thing the early days of Hadoop, but it was cool technically to be you know, putting Hadoop clusters together, and standing them up, but then it's like where's the value? >> I think the Data Lake concept in essence makes a lot of sense. Because you want to get all your data in one central place so you can ask these questions across all the different data types, and all different data sources. The challenge we had was you had the traditional data warehouse which couldn't support the new data types, and the diversity, just pure volume. And then you had newer no SQL like systems like Hadoop that could start to address just the sheer mass of data. But they were so complex that you needed an army, and you still do need an army, and then there's some limitations around performance, and other issues, and so no data projects we're making it into production. I think we still have a very small success rate when you think about data projects that actually make it to production. This is where with Snowflake, because we had the luxury to build it from the ground up, we saw the needs of both using a relational SQL database because SQL is still an amazing expressive language. People have invested skill sets and tools. And then be able to support the new semi-structured data types. All within the same system, right. All within SaaS model so you can start to remove complexity. it's self-managed. We have a self-managed SaaS offering, so customers don't have to worry about all the operational lifting. They can go and get inside to the data. And then because of the cloud they can take advantage of the elasticity in the scale and pay for what they use. >> What was the big bet on Snowflake that paid off. You had to kind of hone it down. >> But the biggest bet John was, we are architecting a database from scratch. Because if you look all the other solutions out there that get the fastest time to market is you can take an architecture that's been existing for a decade or so, and wrap it on a cloud. And that gets you some benefits of the cloud. For instance no need for upfront costs and implementing Hardware in the data center. You can offload some of the management and some of the maintenance to the cloud providers. But like I mentioned before you can't scale automatically. You can't take advantage of infinite scale, right? Because these systems were designed and on-premise role that had a thinking of finite resources. So I think our big bet was, do you create a new architecture. That's a big risk, but luckily it's paid off well. >> Big risk pay offs. Rik talk about the ecosystem. You guys have a big partner strategy. You have to. >> Yep. >> You guys are integrating integration points as comparing to you guys, not the sound like it's in a bad way but, Slack is going public so I'll use them as example. Slack is a software that's cloud-based but what made them really big besides, copying the message board kind of IRC chat, is that they have a huge integration points with all the key players that really fed that in. This is kind of something that in, as a metaphor is not directly directed to you guys but, you guys are very integration partner oriented. >> Yeah >> How is that playing out? Again, I'm sure this, I didn't see any strategy change still continuing. Give us the update, how's that going? It's a great example Snowflake here on theCUBE. This is core of Informatica. Take a minute to explain that strategy. >> Well I think the beginning of the journey of any of our ecosystem partners does start with the connectivity layer. But honestly you know, moving data from point A to point B. That's kind of, that's the tip of the iceberg, right? And so we've really focused on bringing really addressing all the challenges in the entire data journey. So it's one thing about first of all how do I even find the data to bring there. Now once I found it can I connect to it? Do I have the access to the data? Can I bring it to the right targets the customer wants consumed. But then once the data is there, is it usable, is it consumed, is it clean? If I'm doing customer 360, do I need to get my golden records? Or you mentioned GDPR, our whole data protection focus on, you know trying to create a perimeter between different parts of the enterprise, we're automatically applying masking encryption, those sorts of things. So we're really focused on integrating that as tightly as we can and making it seamless for customers to be able to tap into those capabilities when they need them. >> I mean feeding data to machine learning and then powering AI is a great example. If you don't have the right data at the right time for the machine learning, the AI doesn't work well. And then applications that are going to be using machine learning need to have access to data as fast as possible. Lag really hurts everything. This is a huge issue. >> Yeah I mean and we're looking at complete acceleration. You know that whole data discovery phase to build your models and train them. But to your point, garbage in garbage out, right? The old adage is still applicable today, and I think even but you've got security issues. What happens if your training data includes some sensitive code names that show up in your models all of a sudden, right? There's all these issues. But then you take it those models and operationalize them as well. Again, the inputs need to be clean, so. >> Cloud or on-premise, final word. Get your both take on it. Obviously your data warehouse in the cloud. For the customers that have an On-premise dynamic, whether it's legacy or whatever. I got to move to the cloud. I'm eventually going to have some cloud, and how it's going to look. What do they do? What's the State of the Union for dealing with data that's not just in the cloud. >> Yeah. >> Yeah >> You were first, go ahead. >> Yeah sure, I think again going back to having a SAS model, customers can pick specific project specific data sets to go and try out, right? Snowflake gives them a perfect example of, not even having to directly engage the cloud partner yet, right? They want to see if data can be ingested in the cloud in a very fast performant way. They want to see if security meets their needs, right? They want to test out all of the different things around management and ease of use. They can do that with Snowflake. Again, at a very low risk way. Because we are a SaaS platform. We've got a great model on elasticity. The customers can pay as they go just to try it out. So for me, when I think of these customers that are stuck there and trying to make a decision, I say look try Snowflake. It's a very risk-free way to start to analyze some data sets, and if it works for you then you've got a proof point of starting to move more and more workloads into the cloud. >> Rik, digital transformation. What are customers doing? What's the playbook? >> Yeah I think the recipe is, you know, one, the laser focus on value, right? Have you have your eyes on how am I going to get value as quickly as I can this transformation. Second thing is, understand what you have. Understand your existing landscape. That third piece is go. I get started, because I think the case for the cloud is so compelling for customers. I don't know a single customer that I talk with who is not already on the cloud journey. So it's really about making sure you get business value as you proceed down that journey. >> Get the proof points up front. >> Absolutely >> Think smaller steps >> Yep, incremental and casual >> Show the value. Sounds like agility DevOps. Guys thanks for coming on. Good to see you. It's Cube coverage here in Las Vegas, I'm John Furrier. Your host for theCube is Rebeca Night. Two days of wall-to-wall coverage. We'll back with more after this short break. (dramatic music)

>> Produced from the Cube studios. This's strong by science, in depth conversations about science based training, sports performance and all things health and wellness. Here's your hose, Max Marzo. I'm with >> the one and only Cory Slush Inger Cory is the director of men's sorry, director of performance from men's basketball at Stanford University. Good friend of mine, extremely passionate human. And for those you don't know former college basketball Hooper Corey really happened. Happy on a day to thank you for being here. >> No, man, it's an absolute pleasure. Me, Max. It's It's kind of crazy how our relationship has evolved throughout the years. Ah, start with Diem. You know, that's how it usually goes, the way your T shirt and he's got hair. So I wish I was that God, like I got it down here, but I got it out talk. So don't worry, Max. I'm going to make you a T shirt and I'm sending Teo. You said >> make a T shirt. I >> will wear >> until you plant cast with you again. >> Be careful with the pick. Might be >> way careful with that. Wait. Speaking of that, Corey, I mean, before we went on air here, you have a little story about your beard. And not to say you're only known for the beard, but the beer definitely is a staple in the slashing. Your appearance give me back for that. I want to hear it, and they will dive into some of the science. >> Yeah, man. So as far as the beard, I mean, it started at you. Maybe we're on a Spanish tour went overseas, and I did. One of those crazy handlebar mustache is right. I mean, it was gnarly, but being overseas just didn't shave, right? I mean, we're there for almost a week and a half, and I just started growing out the stubble. And then people are like, keep it going. And so I kept going and we were winning a lot of games. And then we end up winning a championship. And so it became like the tournament beard or became like the season beard. And so I just kept rolling it from there, and yeah, that's that's kind of where the beard is stated for now. And then when I realized, like if I could, it almost looks like a cancer patient. So I needed a key because he's blond eyebrows, man from five feet away. It looks like I'm ball period like I can't grow here. So, yeah, that's where the beard states is at this point. >> Well, Iet's fifty. I'm getting mine going. I'm not going to your caliber. I keep it trimmed, but it makes me feel like I'm a scientist or something. If I have a beard, makes you more intelligent, but getting off the topic here. When it comes to developing anybody, people say, you know, athletes, athletes, athletes athletes are what zero point zero zero one percent of population when it comes to developing anybody at all. We got talking about the bass aspects of human movement human development. You have an interesting take on this, and I don't want to spoil it for the listeners. I'd rather have you say it first, cause I'll just bastardized and screw it up. You're going to take on developing anybody regardless if they're an athlete or just general population, >> right? I mean, if you look through human evolution one or two things that we used to do, I used to farm. We used to kill things with our hands. We used to climb, you know, we used to throw things, you know? I mean, look at the the early Olympics, right? I mean, that's basically what the events wass. He wrestled someone. You ran faster than someone. You ran further than someone, and you threw some things. I and basically that's what human capacity is. So my goal before we actually trained them to be better athletes, is to make them better humans first, because if I can express their ability to be a better human, then they will be able to express their ability to be a better athlete. >> Joshua and with those movements, selections. If you have unique choice food people who don't follow up Instagram better weigh on your instagram handle at the end. But the selections of exercises you pick, it's not traditional a sense. Let's load a bar up. Let's do a hand claim you really take ownership of different shaped objects for that way, whether it be a yoke, whether it be a kettle bell, how do you come up with the most movements? Elections? What goes into that decision making? And for any individual out there, whether they are fast ball player who's seven one or a guy who's five eight, how do you decide which of those implements are best fitted for you? >> Well, everything that shaped the way I believe is one hundred ten percent based off my environment. And look, I played college basketball. Don't look at my stats. I was not that good, but I trained in or I've played with, and now for ten years I've trained that basketball athletic population, so you can imagine with me. Okay, I'm five foot ten. Very average, at best, especially with my links, man. Now imagine six foot six, but a seven foot two weeks man and all those things that I was good at, clean snatched jerk. You know, I was a purist in the beginning. I mean, of course I was right. I was just learning what strength iss How to be strong. Now, I'm trying to imagine further. Like, how do I have impact? How do I have quote unquote transfer? What? I'm trying to load these freaks. I mean, these guys are not normal human beings, right? They got seven foot two wings fans and short torso, so their levers are crazy. So now I'm asking them to do the same things that got me strong. Being at five. Ten, it just doesn't make much sense to me now, Not saying they don't have the capacity to do it mean help. Be honest with you. Some of my best weightlifters actually been seven foot tall, But that being said, if there's a way I can load them, that makes a lot more sense. That's easy to teach. I could do it often, and it's right in their comfort zone now, not comfort as in like we're not training hard, but like in their center of mass, where they can actually manipulate loads heavy loads at that with decent speeds. Then, yeah, I'm going to do that. So, for instance, we look at a bar bell, clean snatches all good. Why can't we do the same intent with a trap door? I mean, we could still pull. We could still triple extend and then we can still catch in that power position. The only thing that changes is the complexity of the movement. Now I'm not manipulating myself around a straight bar bell. It's in my centre of mass. And now I, Khun Express quote unquote force. Ah, lot more efficient, Effective. So now I can load it more loaded faster and do less teaching. Yeah, I do that. That makes a lot of things So that's really what it came from. And then to be honest with you, But how do you experience that light? How do you know a seven foot feels like? How do you know? And so you know, I've dabbled town some ways too. Open up my consciousness, if you will, to allow me to feel that ord, allow the imagination, my creativity to tryto understand what that could feel like. And then, of course, obviously feedback from my athletes. But I mean, why you always see, like the old school dues were just like, Oh, this is weak. This is squad. We we box what we what do we do? Whatever to get strong. But it's like, you know, it makes sense. If you're five foot six, it doesn't make much sense if your seven foot tall so you've got a truly find ways to experience it yourself. And now by the means that you do that probably not going to talk about on this podcast. But the way I did it work. >> Yeah, well, we'll refrain from diving that specific. I'd appreciate it on because to each his own one of the things you mentioned like talking about Hooper's I played basketball. I played your Batch three point shooter. Anyone's listening, too, By the way, when my feet are set, I'm not. I'm not an athlete, but I could shoot the shit out of basketball. I'LL be very blunt with you. I've >> been on the receiving end of that on one of our own game. You don't have to talk when you busted my ask way >> down to like. A lot of basketball players are bad movers, and what I mean by that it's their very good when you put a ball in their hands. That is something you talked about, too. But when you get them in a dance room right there, a lot different than football players and I mean by that is you don't see a bad end zone celebration, right? Want touchdown dances look really good, Odell Beckham being very soon and a lot of it's because those patterns are done without a ball in their hand. This is my opinion and they're very primal and natural with a minute and basketball everything's doing the ball in their hand and then when they start to move, especially because they're developing this, you starts. We're like a third rate. Now they have to only play basketball. And typically you don't play football and basketball, especially football. The high level, because you know you prepping for the basketball season itself. >> You get that deal in Scotland. Shit, bro, >> You have to play basketball for every waking hour the next fifteen years to get there. I'm kidding, but I'm thinking about my head is we're not exposed to those different movement. Parents were stuck in this ninety foot unless you're how light is forty six feet, something like that with court that really constrains how we move. And then you put someone in a waiting room where all the son of dealing with external loads and very unique movement patterns you get guys who just looked walking and I think you talked about this on different podcast, but I want to get into a little bit. Here was, I think so. That stems from our coaching of a young athletes and our physical education that we no longer does. Have we used to have back in the day and how that's really affecting athletes as they get older. >> I couldn't agree more. I mean, I get these quote unquote specialized athletes. And to be honest with you, I don't have athletes like I have guys who have a basketball in their hand. They got really long levers and they have some skill, right? They have some skill to be able to go from point A to point B and put on orange round ball into a cellar. That's that's so happen to be ten foot off the ground. That's what I have. I don't have a true athlete who can pick things up off the floor who could sit down on the floor and stand up, who can throw things who can sprint, who could jump onto things. I mean, some of the best vertical jumps that you see in basketball are not even close to what you would see in football and track and field. When you think this is a sport with the high flyers counter movement, jump hands on hips averages that I've seen on teams eighteen inches and everybody is like Oh, that's terrible But that's a true counter movement jump with long levers. So now if we add some momentum to that and add a seven foot two wingspan and then all of a sudden their elbows above the ramp. Right? So that's the difference we get. We see this a NRI or this false thought, or this false vision of what athleticism is because they're so long. But in reality. And then you put a bunch of cornerbacks out there that would be really special to see, because these are guys that are like five foot ten and the most explosive fast dude you've ever seen. There's don't have the skill to play basketball. So you know, with the way we are, physical education is set up now, obviously has been chopped in half, half, half so no more education. Physical education is what we get to. They only play one sport. They sit in chairs that they're not really made to be. They live in this wart western society where every chair they sit in Is that it? His ninety, which for them is more like this, right? And then they get up and down on these beds that their feet are hanging off of. So I don't know what sleep looks like for that. And if you saw my guys get on an airplane, a commercial airplane, you would be cringing the entire time because they're literally bundled up like this. And so not on ly. Are we trying to correct childhood development? I'm trying to correct what they deal with on a daily basis. Just walking the class. We watching my guys duck through door frames constantly. It is like some some of them are guards and they're ducking through frames. And you're just like I don't know how you've made it this far without knocking yourself out. So there's so many that it's really all about the environment and her. When I've trained my athletes, it's all about giving them the environment they have never had. So that's why we utilize the resting room. The gymnastics room. It's soft had so they know, so they don't necessarily fear the ground. They don't fear their interactions gravity. So now I'm giving them the ability to learn how to change levels. You know, little guys. So I don't see six foot ten guys wrestling, right? So I have an opportunity. Now they learn how to interact and change levels, and then even more so you put somebody with them. So now we're like pushing and pulling, just like you see in football. So now they know where they put their feet. So now we're not stepping on feet constantly looking. I mean, God, Hey, these guys are like because sixteen seventeen shoes like, of course, I'm going to step on each other's speed. But if they have that awareness in that sense of where other people are, then maybe they don't make that misstep. Or maybe they get their self out of harm's way and then even more so just learning how to fall. They learn how to fall properly from standing toe floor transitions. Then, when they jumped through the air at forty two inch words, whatever you see, that's make believe for you. Switch vertical right word, but and then they get hit in the air, and now they've got to figure out the most effective way. Not the break there. Nash. Well, most of the guys are going to do everything they can to stay on their feet. Well, that's where you want to get blown out, right? So now if I can give them a tumbling strategy, so now that they can interact with the floor a lot more smoother, athletic, well, then maybe they have a chance to not get hurt and be be back in the action, right? So it's performance enhancing as well as injury mitigation. >> I >> know that. I mean, I don't know where to begin. I have about nine comments off that. First. I love the idea of talking about how these guys are living in a world built for some one, five, ten. I'm six two and Kelsey, my girlfriend. But, hey, can you reach above and grab the top? Can apostle whatever I'm like? Yeah, Okay. But you look at a guy until you actually play hoops. I think, and really appreciate how big these dudes are. You play. It's a guy who's seven one. You look at him and go, Oh, my gosh, like that's at a different human. And then you know his shoe size next to you and you shake his hand and you get to the other side of his hand. You start to understand, like, who we dealing with here, right? You look at these, you know the body needs to heal when it goes into a stress or whatever, and we're putting these guys in positions that the body would not otherwise deem for recovery right now, like this call. Time out. Is that the funniest thing? MBA timeouts. Aside from LeBron James, that's got the nine foot chair right? These guys come out and these will stools that are too small for meaning, and >> so they're not really >> rusting. And you got a dude who's trying to recover his heart rate, but really the whole time, he's in a hip flexion. He's never been in the past, you know, thirty years, right? And if you're thinking about really taking care of an athlete, we spend so much time in the weight room and all this great stuff we can do. So Muchmore. If we had a liberty, too, I use we usually more like you, um, to you, then develop an environment that conducive to them. I know University. Kentucky did that. If you look at their dorm rooms, they had ESPN going on two years ago when they built at the new facility. For the basketball players, the sinks were higher, the magical tired, they were longer. And if you ever wash a guy who's seven foot dragging on the water fountain, I mean the amount of spinal flexion he has to go under. It's ridiculous. The guy's curling up in a C. And I mean, that's crazy to think about because the whole time on the way we were talking about how do we get these guys in a position that they can function successfully? And right now it's like optimally because obviously would have been something we did fifteen years ago to get in a position, right? But how do we get them to be successful? So I pose the question to your court. I'm gonna give you the keys to the castle. The kingdom. Okay, Philip, um, maybe not the whole environment. But there's three things you like to change the outside of the weight room that you had the crystal ball and you could go either back in time more just socially. Okay. I want to change his guys. You know, the size of his car. You know that the chair he sits and we're three things that you pick and dio >> number one. I would get them involved and dance or martial arts as their first sport. That would be probably number one so or gymnastics something. I don't care how tall you are like Who cares if you're not trying Win a gold medal at three, Right? Is just learning how to do those things right? Understanding your body number two. I would change how physical education is and in western society, um, and then number three. Let's give you something actual physical number three. If I could make what? I >> got some for you. Well, you're thinking, OK, I got you want to think your third for me? Basketball players eat horribly. You're so single, teacher. Yeah, basketball players, at least by team. And I will make this universal blanket statement. They just don't like to eat for some reason. Right? Who for? Three hours and drinking game and call it good. And I don't get it like I have a fat ass. My play. I gained weight in season. Really? Team he'll know what a food I take over which you're pulling their postgame meals. And that's when they remove the snack girl. Remember the snack role when, uh, >> you know, you have todo I had Taco Bell, bro. Like we won. We got talking about, you know? So I asked the level Appalachia, which we suck. >> I think I'm going to go a little. Can't you apologize? We're going to go play and that's a D three hoops. That's finest. We're rolling to a game. It's up north took a four hour drive and we stopped at the rude crib an hour and a half before taking a corner booth buffet of ribs. They got a bunch of island boys here. The rib crib you bring up platters were basically, you know, and capacity. And when they get like five points because our center had to pull out the throat at halftime. >> Yeah, it is. Did you ever have to drive the team ban? Because I have ways in the backseat in the bag who thought that was, like level once again, level athlete, that unreal. But I would say that the third thing Don't be wrong. Yes, food. But if there's a way, I mean, if there's a truly economical way across the board to just look, it got health, we could do that, don't care. But I can change your environment that could change your internal environment and will, And the number one is if I can just poof your gut and I can look at everything, then that will be the number one, because just a little moving world. But I don't know how you're absorbing it. I don't know what's going on. And then you wantto talk about these kids that you know, a phD or these kids that are super restless. Well, I think it starts with the gut, because if you're got health sucks, so does this. So that would be the third thing. >> No, that's crazy That way. May I have a little bit of experience is our company. I don't deal with the actual read now that the things I've learned and seeing the idea of taking that integrated approach. So hey, let's actually look at your stomach. Yes, you have to collect your poop three times a day, and I'm sorry. If you're going to do that, you can start to look at what you produced and way of excreting and whether or not you're absorbing what you need to absorb. And we start looking at injuries and no tendon, health and muscle tissue, everything as a holistic approach. What? We gotta look at the internal environment if any of our environments messed up inside and we're trying to impose a stressor on the body. But we have no idea what the internal systems like, and you have certain deficiencies or certain aspects that your lack and these were certain areas where it again people go, Oh, that's not scientific. There's no study. Well, unfortunately, if you understand complex systems and their dynamic interactions and not to get too detail, I'Ll explain it as simple as I can. But what happens is we have an outcome like a strange angle, and we say, Oh, and go weak angle get hurt, right? Well, kind of grooming. Or maybe it's ankle week. That's a risk factor. Athlete didn't sleep enough the past three nights. Risk factor Athlete had some sort of physical contact during the game. That critter there system risk factor athlete. Nutritionally, it wasn't recovering from previous workouts and games. Risk factors so happens of all these risk factors, and that's just a very there's no all the risk factors. A lot involved, all but these risk factors come about and then we have the probabilistic nature of something toe happen. So oh, how likely is it that something bad will go wrong and we see the last straw on the camel's back sprain an ankle and we go a week. But maybe it's didn't sleep enough Ankle week. All this other stuff and that ankle sprain. For people interested in complex systems, it's called an emergent pattern. So there's a common pattern that occurs when you have things go wrong. So if the money C l it's like, Oh, gluten medias is weak knee Val Agus. All right, you're a muscular control all these things that go into and nothing can pinpoint it. So if we're including these bomber, you know about mechanical factors and Eve Alvis, why aren't we including some internal factors like gut health Or, you know, the blood wood for the micro nutrient efficient season? Yes, I know I'm not versed enough to speak on micronutrient deficiencies and our interactions off, you know, health and whatnot. But something as simple as college in environments haven't adequate vitamin C for, you know, ten and healing instead of, you know, repair is obviously a factor. And so when we start looking the bottom, we gotta look at the big picture. It's not just how your knee bends. It's not how you shoot a jump shot. It's not how you land every time. >> Where are you? Our body is so much more resilient and durable than you. Give it credit for me. We've survived as a species. We're a very long time. You're very harsh conditions and you're going to tell me it's that one jump that got you one job. One job is the one that Oh, that needs a little dalliance. That's the one that got you. I mean, if you super slow mo A lot of these great expressions of physical capacity in sport it was you would be like, Oh, my God, they're neither this there that But in reality, like that's I'm close to the reason why they like break or don't Break. And Jordan shallow, brilliant dude, He gave me this metaphor. He was saying to Philip, a pond, Well, it's like this fungus that will Philip a pond and it doubles its size every day. So if it starts off it like, you know, point two, then the next day be point for and he asked me, he's like, Okay, if it's going to Philip in thirty days, Philip, the whole pond, What's the day? It's half full. Then I thought for a second it took me a lot longer than I should have thought about it. But he's like, but he an injection goes day twenty nine. I >> don't want an answer, by the way. >> Yeah, was like Day twenty nine I. That's why I look at the human body like that is literally the last thing and then pull. And so it's all these. We could have had all these interventions from day to today twenty eight or day twenty nine. Even the notes that one just last. Ah, strong. The camel's back to just there goes, you know, And that's what's great about being in the collegiate setting. And being a Stanford is we have a lot of safety nets for our safety, and that's if you will. So we try to have as many quote unquote KP eyes and objective measurements to give us an idea of what could possibly happen. But in reality, it's still the dynamic environment, so I don't understand. Like I can't account for school. I can't account for their sleep. I mean, we could through, like, grouper or or whatever, but it's not realistic and thine and are setting and in their gut hell's like way picking up poop. Three times a day. They were not drawn blood once. We're not doing these things. So unless we're doing that, then you're just trying to create most resilient, durable human beings so they can withstand the stressors some more than others. But hopefully have a successful season. >> No, that's like I hate to break it to people. We don't know what we're doing. We're doing our best. I think chase Wells with him. A Stanford. Get a great line, he said. We can't guarantee success. We can almost guarantee you're not guaranteed to fail. And what I mean by that is that you can't always KP eyes and really, we're looking at. If you jump nine inches, we're probably not going to be very good basketball unless you're seven. No, right. And so we're looking at the human system as a means of understanding what is going on really lagged behind in regards to your performance assessment and what might be hindering you in regards to launch into no tracking? Can I get a little bit of data? A lot? The way explain it is kind of like I don't ask my girlfriend Kelsey, how she's doing. Once a week, you know. I asked her every day and why I asked that every day is to realize, you know, all my clothes that I left out pissing her off. You know, I did. I forget that we're supposed to go on a date last night. You know, I might not have forgot a wallet last night. We went to dinner from now on, Accent, all supposed to buy. But that's a true story. WeII >> brought up. I mean, that's the most important thing is you gotta have feedback daily, right? And wait here. It's really simple. We take a controlled environment, do some things in it before they go into a dynamic environment, which is basketball games of basketball practice. So what we do is we call that microdot. It's our way of training. Every day, in some form or fashion, these individuals come into their work, their human capacity, a Siri's, if you will. Then after that, they go into their B series, which is complex. This is really what I know what's going on. I don't get me wrong when they walk in to get their weight, are joking or making eye contact and get that handshake. How firm is that handshake thes air, All the quantitative things that I'm trying to pick up as they're coming through the door. Then you watch them say We're hitting clean, complex and they're going through the motions and their consulate changing grip or or the pool isn't looking too good, and any sharp today will boom. That's my control Now. It's not the most objective feedback, but at least it's a constant. And so that's my way of having once against safety nets from a safety nets and then weekly or depending on how many games we have that we do, our force plate jumps. So once again, another safety net, and then we have our connects on day. So our GPS data that they do on the practice gym once again any one of those in isolation doesn't tell me much. But if I have a bunch of them, then I can at least paint a better picture from quantitative qualitative, and then I can go and knit. Pick what I think they're intervention may need to be, and so it's not going to be perfect, not even close, but as long as you have a constant and yours is beautiful. Like you said, Just something simple. You get daily. Hey, how are you doing? And you know how they express that. I'm doing good. I'm doing good. I'm cool. I'm great. Like, you know, what there was in flux is are like, you know what? They're how they're truly feeling. Just based off that one question alone. But once again, if you can set up your system or your program or whatever toe have safety nets for your safety nets, then I think you can You can catch a >> lot of those along the way. >> Yeah. No, that makes sense. It's how you provide context to a situation. And the more information that we can apply that we didn't classifier more to a system like jumping is, you know, your lower body strength and your verbal expressions, your most emotional state on DH, maybe even sweep or other things that go into that, the more we could understand what's actually happening to the person. So I was kind of really bad for a second. You said some of micro dose in and term overdose. You refer into training a little bit often. Yep. And Corey is well known for this and for those at home listening, I'm going to my best to explain it. Short weeks. I got a question off of it. If you know, explains it will stay here for another hour and a half because great to listen to. But I want Teo a little bit of a different direction off of athletics about it. Firstly, micro doses the idea that we're applying a moderate level toe, low level stressor consistently, and that adaptation occurs from the aggravation off those dresses over a period of time. So we're never going to Hi, we're never going to low. And the idea is that training in the weight room is only one small piece of your life. They even programmed High Day, and you don't sleep that night or you have emotional stressor for your case, your practice. Then all of a sudden, that high, big, magnified and starts spilling over the bar and becomes too much the idea of micro dozing, especially a non controlled external environment where it's called life, and we're trying to apply enough that you can handle. If someone's feeling good, then they can push a little bit that they themselves. Now My question for you, Cory, is I love an athletic sense. I also see it being very applicable to anyone out there general population and especially in terms of I got two things. Us too. In terms of one, someone learned a movement. You get a chance to do it often and daily and someone who wants to learn how to be in the weight room. And secondly, because there are, let's say we do it eight out of ten days. If you only miss one day, you're only missing ten percent of your entire workout, right? So instead of doing looking at this whole one workout one day, you look at like a ten day period. If you got eight days of pick from and you just can't do one, you only missed ten percent versus if you only had five days of pick one and you miss one, you missed twenty percent, right? And so now we have the ability to be more flexible in our environment. So how does that fit in like a general population? If it was my dad or my girlfriend trying to learn howto use some of this micro dose in the weight room. How do you plan? >> So one hundred percent with micro dozing. The reason why it came about was it was a solution to a problem. My problem is I don't have enough exposure to my guys. So how do I create more training frequency? And now we got rid of warm up something that was just kind of getting them ready for practice. That kind of don't care about it. The coach hated seen me do it. I personally hated doing it. So now it was a solution. What it turned into was motor learning. Now you want to learn how to train, will do it all the time. So that's where complex comes in. It's the value of orcs work, right? So basically, you take a bar bill and you do every movement that you would do in a weight room, in some sense, in one set, so you'd hinge You do a hip flexion. You do a press, do a pool. If I break down each one of those into isolation, it would look like already else Squad, Polish, military, press or row, those air all movements that you would do and if you separated each exercise in an isolation you would go more resistance on, just like you would see in general fitness, right? Like we're going to do three sets of ten on bench press or three sets a tent on back squad. Well, that's great. How about we just put it all in one and now we have more exposure. So now I'm learning how to do the movements, and then you can't tell me that doing one thing once a week is actually going to make you learn the movement. So now you learn those little small video sequences that you see with thirty year experience power lifters who truly understand, like, move from body, this foot stance, or this is how I start to hinge here within my squat X degree. And that's how they perfected is because they have so much exposure to it. So we're doing the same thing. We're just trying to create exposure at lower thresholds and and in doing it often now as faras general population, what's the number one concern? But I don't have enough time. Oh, really? You don't have a thirty minute today, twenty to thirty minutes a day to not kind ofwork. Now. Every day I call B s. I say You just don't want to train. So that's where my producing to me is beautiful in the general population is because it's living the way you start your day. It's lunch, or it's when you get off work. Perfect. You can pick any of those three slots twenty, thirty minutes. You can eat and shower and get backto work or before work. So you can't tell me that everybody doesn't have that situation. So now, creating training frequency, you're getting enough volume throughout the week. Now we have on and then most importantly, like you brought up if I just had to miss that one day, it's ten percent of my training like it's not well, only train twice a week, So fifty percent of my training is gone. So that's where I think it's beautiful. And that's where he could work from general population to the most elite athletes in the world and the reason why I say the most elite athletes in the world because I just so happen to train to of So I do it with all these populations

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Okay. Welcome back, everyone. He live in San Francisco. Here on Mosconi St for the cubes. Exclusive coverage of IBM. Think twenty nineteen. I'm Jeffrey David Long. Four days of coverage bringing on all the action talking. The top executives, entrepreneurs, ecosystem partners and everyone who can bring the signal from the noise here on the Q and excuses. Rob Thomas, general manager, IBM Data and a I with an IBM Cube Alumni. Great to see you again. >> Great. There you go. >> You read a >> book yet? This year we've written ten books on a data. Your general manager. There's >> too much work. Not enough time >> for that's. Good sign. It means you're working hard. Okay. Give us give us the data here because a I anywhere in the center of the announcements we have a story up on. Slick earnings have been reported on CNBC. John Ford was here earlier talking to Ginny. This is a course centerpiece of it. Aye, aye. On any cloud. This highlights the data conversation you've been part of. Now, I think what seven years seems like more. But this is now happening. Give us your thoughts. >> Go back to basics. I've shared this with you before. There's no AI without IA, meaning you need an information architecture to support what you want to do in AI. We started looking into that. Our thesis became so clients are buying into that idea. The problem is their data is everywhere onpremise, private cloud, multiple public clouds. So our thesis became very simple. If we can bring AI to the data, it will make Watson the leading AI platform. So what we announced wtih Watson Anywhere is you could now have it wherever your data is public, private, any public cloud, build the models, run them where you want. I think it's gonna be amazing >> data everywhere and anywhere. So containers are big role in This is a little bit of a deb ops. The world you've been living in convergence of data cloud. How does that set for clients up? What are they need to know about this announcement? Was the impact of them if any >> way that we enable Multi Cloud and Watson anywhere is through IBM cloud private for data? That's our data Micro services architectural writing on Cooper Netease that gives you the portability so that it can run anywhere because, in addition Teo, I'd say, Aye, aye, ambitions. The other big client ambition is around how we modernize to cloud native architectures. Mohr compose herbal services, so the combination gets delivered. Is part of this. >> So this notion of you can't have a eye without a it's It's obviously a great tagline. You use it a lot, but it's super important because there's a gap between those who sort of have a I chops and those who don't. And if I understand what you're doing is you're closing that gap by allowing you to bring you call that a eye to the data is it's sort of a silo buster in regard. Er yeah, >> the model we use. I called the eye ladder. So they give it as all the levels of sophistication an organization needs to think about. From how you collect data, how you organize data, analyze data and then infused data with a I. That's kind of the model that we used to talk about. Talk to clients about that. What we're able to do here is same. You don't have to move your data. The biggest problem Modi projects is the first task is OK move a bunch of data that takes a lot of time. That takes a lot of money. We say you don't need to do that. Leave your data wherever it is. With Cloud private for data, we can virtualized data from any source. That's kind of the ah ha moment people have when they see that. So we're making that piece really >> easy. What's the impact this year and IBM? Think to the part product portfolio. You You had data products in the past. Now you got a eye products. Any changes? How should people live in the latter schism? A kind of a rubric or a view of where they fit into it? But what's up with the products and he changes? People should know about? >> Well, we've brought together the analytics and I units and IBM into this new organization we call Dayton ay, ay, that's a reflection of us. Seen that as two sides of the same coin. I really couldn't really keep them separate. We've really simplified how we're going to market with the Watson products. It's about how you build run Manager II watching studio Watson Machine Learning Watson Open scale. That's for clients that want to build their own. Aye, aye. For clients that wants something out of the box. They want an application. We've got Watson assistant for customer service. Watson Discovery, Watson Health Outset. So we've made it really easy to consume Watson. Whether you want to build your own or you want an application designed for the line of business and then up and down the data, stack a bunch of different announcements. We're bringing out big sequel on Cloudera as part of our evolving partnership with the new Cloudera Horn Works entity. Virtual Data Pipeline is a partnership that we've built with active fio, so we're doing things at all layers of the last. >> You're simplifying the consumption from a client, your customer perspective. It's all data. It's all Watson's, the umbrella for brand for everything underneath that from a tizzy, right? >> Yeah, Watson is the Aye, aye, brand. It is a technology that's having an impact. We have amazing clients on stage with this this week talking about, Hey, Eyes No longer. I'd like to say I was not magic. It's no longer this mystical thing. We have clients that are getting real outcomes. Who they II today we've got Rollback of Scotland talking about how they've automated and augmented forty percent of their customer service with watching the system. So we've got great clients talking about other using >> I today. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. Aye, aye. Some customers wanted out of the box. What? The patterns that you're seeing in terms of who wants to do their own. Aye. Aye. Why do they want to do their own, eh? I do. They get some kind of competitive advantage. So they have additional skill sets that they need. >> It's a >> It's a maker's mark. It is how I would describe it. There's a lot of people that want to make their own and try their own. Ugh. I think most organizations, they're gonna end up with hundreds of different tools for building for running. This is why we introduced Watson Open Scale at the end of last year. That's How would you manage all of your A II environments? What did they come from? IBM or not? Because you got the and the organization has to have this manageable. Understandable, regardless of which tool they're using. I would say the biggest impact that we see is when we pick a customer problem. That is widespread, and the number one right now is customer service. Every organization, regardless of industry, wants to do a better job of serving clients. That's why Watson assistant is taking off >> this's. Where? Data The value of real time data. Historical data kind of horizontally. Scaleable data, not silo data. We've talked us in the past. How important is to date a quality piece of this? Because you have real time and you have a historical date and everything in between that you had to bring to bear at low ladened psi applications. Now we're gonna have data embedded in them as a feature. Right. How does this change? The workloads? The makeup of you? Major customer services? One piece, the low hanging fruit. I get that. But this is a key thing. The data architecture more than anything, isn't it? >> It is. Now remember, there's there's two rungs at the bottom of the ladder on data collection. We have to build a collect data in any form in any type. That's why you've seen us do relationships with Mongo. D B. Were they ship? Obviously with Claude Era? We've got her own data warehouse, so we integrate all of that through our sequel engine. That thing gets to your point around. Are you gonna organize the data? How are you going to curate it? We've got data catalogue. Every client will have a data catalogue for many dollar data across. Clouds were now doing automated metadata creation using a I and machine learning So the organization peace. Once you've collected it than the organization, peace become most important. Certainly, if you want to get to self service analytics, you want to make data available to data scientists around the organization. You have to have those governance pieces. >> Talk about the ecosystem. One of the things that's been impressive IBM of the years is your partnerships. You've done good partners. Partnership of relationships now in an ecosystem is a lot of building blocks. There's more complexity requires software to distract him away. We get that. What's opportunities for you to create new relationships? Where are the upper opportunities for someone a developer or accompanied to engage with you guys? Where's the white spaces? Where is someone? Take advantage of your momentum and you're you're a vision. >> I am dying for partners that air doing domain specific industry specific applications to come have them run on IBM cloud private for data, which unleashes all the data they need to be a valuable application. We've already got a few of those data mirrors. One sensing is another one that air running now as industry applications on top of IBM Club private for data. I'd like to have a thousand of these. So all comers there. We announced a partnership with Red Hat back in May. Eventually, that became more than just a partnership. But that was about enabling Cloud Private, for data on red had open shift, So we're partnered at all layers of the stack. But the greatest customer need is give me an industry solution, leveraging the best of my data. That's why I'm really looking for Eyes V. Partners to run on Ivan clubs. >> What's your pitch to those guys? Why, why I should be going. >> There is no other data platform that will connect to all your data sources, whether they're on eight of us as your Google Cloud on premise. So if you believe data is important to your application. There's simply no better place to run than IBM. Claude Private for data >> in terms of functionality, breath o r. Everything >> well, integrating with all your data. Normally they have to have the application in five different places. We integrate with all the data we build the data catalogue. So the data's organized. So the ingestion of the data becomes very easy for the Iast V. And by the way, thirdly, IBM has got a pretty good reach. Globally, one hundred seventy countries, business partners, resellers all over the world, sales people all over the world. We will help you get your product to market. That's a pretty good value >> today. We talk about this in the Cube all the time. When the cloud came, one of the best things about the cloud wasn't allowed. People to put applications go there really quickly. Stand them up. Startups did that. But now, in this domain world of of data with the clouds scale, I think you're right. I think domain X expertise is the top of the stack where you need specially special ism expertise and you don't build the bottom half out. What you're getting at is of Europe. If you know how to create innovation in the business model, you could come in and innovate quickly >> and vertical APS don't scale enough for me. So that's why focus on horizontal things like customer service. But if you go talk to a bank, sometimes customer service is not in office. I want to do something in loan origination or you're in insurance company. I want to use their own underwriting those air, the solutions that will get a lot of value out of running on an integrated data start >> a thousand flowers. Bloom is kind of ecosystem opportunity. Looking forward to checking in on that. Thoughts on on gaps. For that you guys want to make you want to do em in a on or areas that you think you want to double down on. That might need some help, either organic innovation or emanate what areas you looking at. Can you share a little bit of direction on that? >> We have, >> ah, a unique benefit. And IBM because we have IBM research. One of their big announcement this week is what we call Auto Way I, which is basically automating the process of feature engineering algorithm selection, bringing that into Watson Studio and Watson Machine learning. I am spending most of my time figure out howto I continue to bring great technology out of IBM research and put in the hand of clients through our products. You guys solve the debaters stuff yesterday. We're just getting started with that. We've got some pretty exciting organic innovation happen in IBM. >> It's awesome. Great news for startups. Final question for you. For the folks watching who aren't here in San Francisco, what's the big story here? And IBM think here in San Francisco. Big event closing down the streets here in Howard Street. It's huge. What's the big story? What's the most important things happening? >> The most important thing to me and the customer stories >> here >> are unbelievable. I think we've gotten past this point of a eyes, some idea for the future we have. Hundreds of clients were talking about how they did an A I project, and here's the outcome they got. It's really encouraging to see what I encourage. All clients, though, is so build your strategy off of one big guy. Project company should be doing hundreds of Aye, aye projects. So in twenty nineteen do one hundred projects. Half of them will probably fail. That's okay. The one's that work will more than make up for the ones that don't work. So we're really encouraging mass experimentation. And I think the clients that air here are, you know, creating an aspirational thing for things >> just anecdotally you mentioned earlier. Customer service is a low hanging fruit. Other use cases that are great low hanging fruit opportunities for a >> data discovery data curation these air really hard manual task. Today you can start to automate some of that. That has a really big impact. >> Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio. Watson Rob. Great to see you conventionally on all your success. But following you from the beginning. Great momentum on the right way. Thanks. Gradually. More cute coverage here. Live in San Francisco from Mosconi North. I'm John for Dave A lot. They stay with us for more coverage after this short break

[Music] when welcome to the special exclusive cube conversation here in Palo Alto in our studios I'm John for your host of the cube we have a very special guest speaking for the first time around some alleged alleged accusations and also innuendo around the Amazon Web Services Jedi contract and his firm c5 capital our guest as Andre Pienaar who's the founder of c5 capital Andre is here for the first time to talk about some of the hard conversations and questions surrounding his role his firm and the story from the BBC Andre thanks for a rat for meeting with me John great to have me thank you so you're at the center of a controversy and just for the folks who know the cube know we interviewed a lot of people I've interviewed you at Amazon web sources summit Teresa Carl's event and last year I met you and bought a rein the work you're doing there so I've met you a few times so I don't know your background but I want to drill into it because I was surprised to see the BBC story come out last week that was basically accusing you of many things including are you a spy are you infiltrating the US government through the Jedi contract through Amazon and knowing c-5 capital I saw no correlation when reading your article I was kind of disturbed but then I saw I said a follow-on stories it just didn't hang together so I wanted to press you on some questions and thanks for coming in and addressing them appreciate it John thanks for having me so first thing I want to ask you is you know it has you at the center this firm c5 capital that you the founder of at the center of what looks like to be the fight for the big ten billion dollar DoD contract which has been put out to multiple vendors so it's not a single source deal we've covered extensively on silicon angle calm and the cube and the government the government Accounting Office has ruled that there are six main benefits of going with a sole provider cloud this seems to be the war so Oracle IBM and others have been been involved we've been covering that so it kind of smells like something's going along with the story and I just didn't believe some of the things I read and I want to especially about you and see five capitals so I want to dig into what the first thing is it's c5 capital involved in the Jedi contract with AWS Sean not at all we have absolutely no involvement in the Jedi contract in any way we're not a bidder and we haven't done any lobbying as has been alleged by some of the people who've been making this allegation c5 has got no involvement in the general contract we're a venture capital firm with a British venture capital firm we have the privilege of investing here in the US as a foreign investor and our focus really is on the growth and the success of the startups that we are invested in so you have no business interest at all in the deal Department of Defense Jedi contract none whatsoever okay so to take a minute to explain c5 firm I read some of the stories there and some of the things were intricate structures of c5 cap made it sound like there was like a cloak-and-dagger situation I want to ask you some hard questions around that because there's a link to a Russian situation but before we get to there I want to ask you explain what is c5 capital your mission what are the things that you're doing c5 is a is a British venture capital firm and we are focused on investing into fast-growing technology companies in three areas cloud computing cyber security and artificial intelligence we have two parts our business c5 capital which invests into late stage companies so these are companies that typically already have revenue visibility and profitability but still very fast-growing and then we also have a very early stage startup platform that look at seed state investment and this we do through two accelerators to social impact accelerators one in Washington and one in Bahrain and it's just size of money involved just sort of order magnitude how many funds do you have how is it structure again just share some insight on that is it is there one firm is there multiple firms how is it knows it work well today the venture capital business has to be very transparent it's required by compliance we are a regulated regulated firm we are regulated in multiple markets we regulated here in the US the sec as a foreign investor in london by the financial conduct authority and in Luxembourg where Afonso based by the regulatory authorities there so in the venture capital industry today you can't afford to be an opaque business you have to be transparent at all levels and money in the Western world have become almost completely transparent so there's a very comprehensive and thorough due diligence when you onboard capital called know your client and the requirements standard requirement now is that whenever you're onboard capital from investor you're gonna take it right up to the level of the ultimate beneficial ownership so who actually owns this money and then every time you invest and you move your money around it gets diligence together different regulators and in terms of disclosure and the same applies often now with clients when our portfolio companies have important or significant clients they also want to know who's behind the products and the services they receive so often our boards our board directors and a shell team also get diligence by by important clients so explain this piece about the due diligence and the cross country vetting that goes on is I think it's important I want to get it out because how long has been operating how many deals have you done you mentioned foreign investor in the United States you're doing deals in the United States I know I've met one of your portfolio companies at an event iron iron on it iron net general Keith Alexander former head of the NSA you know get to just work with him without being vetted I guess so so how long a c5 capital been in business and where have you made your investments you mentioned cross jurisdiction across countries whatever it's called I don't know that so we've been and we've been in existence for about six years now our main focus is investing in Europe so we help European companies grow globally Europe historically has been underserved by venture capital we on an annual basis we invest about twenty seven billion dollars gets invested in venture capital in Europe as opposed to several multiples of that in the US so we have a very important part to play in Europe to how European enterprise software companies grow globally other important markets for us of course are Israel which is a major center of technology innovation and and the Middle East and then the u.s. the u.s. is still the world leader and venture capital both in terms of size but also in terms of the size of the market and of course the face and the excitement of the innovation here I want to get into me early career because again timing is key we're seeing this with you know whether it's a Supreme Court justice or anyone in their career their past comes back to haunt them it appears that has for you before we get there I want to ask you about you know when you look at the kind of scope of fraud and corruption that I've seen in just on the surface of government thing the government bit Beltway bandits in America is you got a nonprofit that feeds a for-profit and then what you know someone else runs a shell corporation so there's this intricate structures and that word was used which it kind of implies shell corporations a variety of backroom kind of smokey deals going on you mentioned transparency I do you have anything to hide John in in in our business we've got absolutely nothing to hide we have to be transparent we have to be open if you look at our social media profile you'll see we are communicating with the market almost on a daily basis every time we make an investment we press release that our website is very clear about who's involved enough who our partners are and the same applies to my own personal website and so in terms of the money movement around in terms of deploying investments we've seen Silicon Valley VCS move to China get their butts handed to them and then kind of adjust their scenes China money move around when you move money around you mentioned disclosure what do you mean there's filings to explain that piece it's just a little bit so every time we make an investment into a into a new portfolio company and we move the money to that market to make the investment we have to disclose who all the investors are who are involved in that investment so we have to disclose the ultimate beneficial ownership of all our limited partners to the law firms that are involved in the transactions and those law firms in turn have applications in terms of they own anti-money laundering laws in the local markets and this happens every time you move money around so I I think that the level of transparency in venture capital is just continue to rise exponentially and it's virtually impossible to conceal the identity of an investor this interesting this BBC article has a theme of national security risk kind of gloom and doom nuclear codes as mentioned it's like you want to scare someone you throw nuclear codes at it you want to get people's attention you play the Russian card I saw an article on the web that that said you know anything these days the me2 movement for governments just play the Russian card and you know instantly can discredit someone's kind of a desperation act so you got confident of interest in the government national security risk seems to be kind of a theme but before we get into the BBC news I noticed that there was a lot of conflated pieces kind of pulling together you know on one hand you know you're c5 you've done some things with your hat your past and then they just make basically associate that with running amazon's jedi project yes which i know is not to be true and you clarified that joan ends a problem joan so as a venture capital firm focused on investing in the space we have to work with all the Tier one cloud providers we are great believers in commercial cloud public cloud we believe that this is absolutely transformative not only for innovation but also for the way in which we do venture capital investment so we work with Amazon Web Services we work with Microsoft who work with Google and we believe that firstly that cloud has been made in America the first 15 companies in the world are all in cloud companies are all American and we believe that cloud like the internet and GPS are two great boons which the US economy the u.s. innovation economy have provided to the rest of the world cloud computing is reducing the cost of computing power with 50 percent every three years opening up innovation and opportunities for Entrepreneurship for health and well-being for the growth of economies on an unprecedented scale cloud computing is as important to the global economy today as the dollar ease as the world's reserve currency so we are great believers in cloud we great believers in American cloud computing companies as far as Amazon is concerned our relationship with Amazon Amazon is very Amazon Web Services is very clear and it's very defined we participate in a public Marcus program called AWS activate through which AWS supports hundreds of accelerators around the world with know-how with mentoring with teaching and with cloud credits to help entrepreneurs and startups grow their businesses and we have a very exciting focus for our two accelerators which is on in Washington we focus on peace technology we focus on taking entrepreneurs from conflict countries like Sudan Nigeria Pakistan to come to Washington to work on campus in the US government building the u.s. Institute for peace to scale these startups to learn all about cloud computing to learn how they can grow their businesses with cloud computing and to go back to their own countries to build peace and stability and prosperity their heaven so we're very proud of this mission in the Middle East and Bahrain our focus is on on female founders and female entrepreneurs we've got a program called nebula through which we empower female founders and female entrepreneurs interesting in the Middle East the statistics are the reverse from what we have in the West the majority of IT graduates in the Middle East are fimo and so there's a tremendous talent pool of of young dynamic female entrepreneurs coming out of not only the Gulf but the whole of the MENA region how about a relation with Amazon websites outside of their normal incubators they have incubators all over the place in the Amazon put out as Amazon Web Services put out a statement that said hey you know we have a lot of relationships with incubators this is normal course of business I know here in Silicon Valley at the startup loft this is this is their market filled market playbook so you fit into that is that correct as I'm I get that that's that's absolutely correct what we what is unusual about a table insists that this is a huge company that's focused on tiny startups a table started with startups it double uses first clients with startups and so here you have a huge business that has a deep understanding of startups and focus on startups and that's enormous the attractor for us and terrific for our accelerators department with them have you at c5 Capitol or individually have any formal or conversation with Amazon employees where you've had outside of giving feedback on products where you've tried to make change on their technology make change with their product management teams engineering you ever had at c5 capital whore have you personally been involved in influencing Amazon's product roadmap outside they're just giving normal feedback in the course of business that's way above my pay grade John firstly we don't have that kind of technical expertise in C 5 C 5 steam consists of a combination of entrepreneurs like myself people understand money really well and leaders we don't have that level of technical expertise and secondly that's what one our relationship with AWS is all about our relationship is entirely limited to the two startups and making sure that the two accelerators in making sure that the startups who pass through those accelerators succeed and make social impact and as a partner network component Amazon it's all put out there yes so in in a Barren accelerator we've we formed part of the Amazon partner network and the reason why we we did that was because we wanted to give some of the young people who come through the accelerator and know mastering cloud skills an opportunity to work on some real projects and real live projects so some of our young golf entrepreneurs female entrepreneurs have been working on building websites on Amazon Cloud and c5 capital has a relationship with former government officials you funded startups and cybersecurity that's kind of normal can you explain that positioning of it of how former government if it's whether it's US and abroad are involved in entrepreneurial activities and why that is may or may not be a problem certainly is a lot of kind of I would say smoke around this conversation around coffin of interest and you can you explain intelligence what that was it so I think the model for venture capital has been evolving and increasingly you get more and more differentiated models one of the key areas in which the venture capital model is changed is the fact that operating partners have become much more important to the success of venture capital firms so operating partners are people who bring real world experience to the investment experience of the investment team and in c-five we have the privilege of having a terrific group of operating partners people with both government and commercial backgrounds and they work very actively enough firm at all levels from our decision-making to the training and the mentoring of our team to helping us understand the way in which the world is exchanging to risk management to helping uh portfolio companies grow and Silicon Valley true with that to injuries in Horowitz two founders mr. friendly they bring in operating people that have entrepreneurial skills this is the new model understand order which has been a great source of inspiration to us for our model and and we built really believe this is a new model and it's really critical for the success of venture capitals to be going forward and the global impact is pretty significant one of things you mentioned I want to get your take on is as you operate a global transaction a lots happened a lot has to happen I mean we look at the ICO market on the cryptocurrency side its kind of you know plummeting obsoletes it's over now the mood security children's regulatory and transparency becomes critical you feel fully confident that you haven't you know from a regulatory standpoint c5 capital everything's out there absolutely risk management and regulated compliance and legal as the workstream have become absolutely critical for the success of venture capital firms and one of the reasons why this becomes so important John is because the venture capital world over the last few years have changed dramatically historically all the people involved in venture capital had very familiar names and came from very familiar places over the last few years with a diversification of global economic growth we've seen it's very significant amounts of money being invest invested in startups in China some people more money will invest in startups this year in China than in the US and we've seen countries like Saudi Arabia becoming a major source of venture capital funding some people say that as much as 70% of funding rounds this year in some way or another originated from the Gulf and we've seen places like Russia beginning to take an interest in technology innovation so the venture capital world is changing and for that reason compliance and regulation have become much more important but if Russians put 200 million dollars in face book and write out the check companies bright before that when the after 2008 we saw the rise of social networking I think global money certainly has something that I think a lot of people start getting used to and I want on trill down into that a little bit we talked about this BBC story that that hit and the the follow-on stories which actually didn't get picked up was mostly doing more regurgitation of the same story but one of the things that that they focus in on and the story was you and the trend now is your past is your enemy these days you know they try to drum up stuff in the past you've had a long career some of the stuff that they've been bringing in to paint you and the light that they did was from your past so I wanted to explore that with you I know you this is the first time you've talked about this and I appreciate you taking the time talk about your early career your background where you went to school because the way I'm reading this it sounds like you're a shady character I like like I interviewed on the queue but I didn't see that but you know I'm going to pressure here for that if you don't mind I'd like to to dig into that John thank you for that so I've had the I've had the privilege of a really amazingly interesting life and at the heart of at the heart of that great adventures been people and the privilege to work with really great people and good people I was born in South Africa I grew up in Africa went to school there qualified as a lawyer and then came to study in Britain when I studied international politics when I finished my studies international politics I got head hunted by a US consulting firm called crow which was a start of a 20 years career as an investigator first in crawl where I was a managing director in the London and then in building my own consulting firm which was called g3 and all of this led me to cybersecurity because as an investigator looking into organized crime looking into corruption looking into asset racing increasingly as the years went on everything became digital and I became very interested in finding evidence on electronic devices but starting my career and CRO was tremendous because Jules Kroll was a incredible mentor he could walk through an office and call everybody by their first name any Kroll office anywhere in the world and he always took a kindly interest in the people who work for him so it was a great school to go to and and I worked on some terrific cases including some very interesting Russian cases and Russian organized crime cases just this bag of Kroll was I've had a core competency in doing investigative work and also due diligence was that kind of focus yes although Kroll was the first company in the world to really have a strong digital practice led by Alan Brugler of New York Alan established the first computer forensics practice which was all focused about finding evidence on devices and everything I know about cyber security today started with me going to school with Alan Brolin crawl and they also focused on corruption uncovering this is from Wikipedia Kroll clients help Kroll helps clients improve operations by uncovering kickbacks fraud another form of corruptions other specialty areas is forensic accounting background screening drug testing electronic investigation data recovery SATA result Omar's McLennan in 2004 for 1.9 billion mark divested Kroll to another company I'll take credit risk management to diligence investigator in Falls Church Virginia over 150 countries call Kroll was the first CRO was the first household brand name in this field of of investigations and today's still is probably one of the strongest brand names and so it was a great firm to work in and was a great privilege to be part of it yeah high-end high-profile deals were there how many employees were in Kroll cuz I'd imagine that the alumni that that came out of Kroll probably have found places in other jobs similar to yes do an investigative work like you know they out them all over the world many many alumni from Kroll and many of them doing really well and doing great work ok great so now the next question want to ask you is when you in Kroll the South Africa connection came up so I got to ask you it says business side that you're a former South African spy are you a former South African spy no John I've never worked for any government agency and in developing my career my my whole focus has been on investigations out of the Kroll London office I did have the opportunity to work in South Africa out of the Kroll London office and this was really a seminal moment in my career when I went to South Africa on a case for a major international credit-card company immediately after the end of apartheid when democracy started to look into the scale and extent of credit card fraud at the request of this guy what year was there - how old were you this was in 1995 1996 I was 25 26 years old and one of the things which this credit card company asked me to do was to assess what was the capability of the new democratic government in South Africa under Nelson Mandela to deal with crime and so I had the privilege of meeting mr. Mandela as the president to discuss this issue with him and it was an extraordinary man the country's history because there was such an openness and a willingness to to address issues of this nature and to grapple with them so he was released from prison at that time I remember those days and he became president that's why he called you and you met with him face to face of a business conversation around working on what the future democracy is and trying to look at from a corruption standpoint or just kind of in general was that what was that conversation can you share so so that so the meeting involved President Mandela and and the relevant cabinet ministers the relevant secretaries and his cabinet - responsible for for these issues and the focus of our conversation really started with well how do you deal with credit card fraud and how do you deal with large-scale fraud that could be driven by organized crime and at the time this was an issue of great concern to the president because there was bombing in Kate of a Planet Hollywood cafe where a number of people got very severely injured and the president believed that this could have been the result of a protection racket in Cape Town and so he wanted to do something about it he was incredibly proactive and forward-leaning and in an extraordinary way he ended the conversation by by asking where the Kroll can help him and so he commissioned Kroll to build the capacity of all the black officers that came out of the ANC and have gone into key government positions on how to manage organized crime investigations it was the challenge at that time honestly I can imagine apartheid I remember you know I was just at a college that's not properly around the same age as you it was a dynamic time to say the least was his issue around lack of training old school techniques because you know that was right down post-cold-war and then did what were the concerns not enough people was it just out of control was it a corrupt I mean just I mean what was the core issue that Nelson wanted to hire Kroll and you could work his core issue was he wanted to ensure the stability of South Africa's democracy that was his core focus and he wanted to make South Africa an attractive place where international companies felt comfortable and confident in investing and that was his focus and he felt that at that time because so many of the key people in the ANC only had training in a cold war context that there wasn't a Nessy skill set to do complex financial or more modern investigations and it was very much focused he was always the innovator he was very much focused on bringing the best practices and the best investigative techniques to the country he was I felt in such a hurry that he doesn't want to do this by going to other governments and asking for the help he wanted to Commission it himself and so he gave he gave a crawl with me as the project leader a contract to do this and my namesake Francois Pienaar has become very well known because of the film Invictus and he's been he had the benefit of Mandela as a mentor and as a supporter and that changed his career the same thing happened to me so what did he actually asked you to do was it to train build a force because there's this talk that and was a despite corruption specifically it was it more both corruption and or stability because they kind of go hand in hand policy and it's a very close link between corruption and instability and and president Ellis instructions were very clear to Crowley said go out and find me the best people in the world the most experienced people in the world who can come to South Africa and train my people how to fight organized crime so I went out and I found some of the best people from the CIA from mi6 the British intelligence service from the Drug Enforcement Agency here in the US form officers from the Federal Bureau of Investigation's detectives from Scotland Yard prosecutors from the US Justice Department and all of them for a number of years traveled to South Africa to train black officers who were newly appointed in key roles in how to combat organized crime and this was you acting as an employee he had crow there's not some operative this is he this was me very much acting as a as an executive and crow I was the project leader Kroll was very well structured and organized and I reported to the chief executive officer in the London office nor Garret who was the former head of the CIA's Near East Division and Nelson Mandela was intimately involved in this with you at Krall President Mandela was the ultimate support of this project and he then designated several ministers to work on it and also senior officials in the stories that had been put out this past week they talked about this to try to make it sound like you're involved on two sides of the equation they bring up scorpions was this the scorpions project that they referred to so it was the scorpions scorpion sounds so dangerous and a movie well there's a movie a movie does feature this so at the end of the training project President Mandela and deputy president Thabo Mbeki who subsequently succeeded him as president put together a ministerial committee to look at what should they do with the capacity that's been built with this investment that they made because for a period of about three years we had all the leading people the most experienced people that have come out of some of the best law enforcement agencies and some of the best intelligence services come and trained in South Africa and this was quite this was quite something John because many of the senior officers in the ANC came from a background where they were trained by the opponents of the people came to treat trained them so so many of them were trained by the Stasi in East Germany some of them were trained by the Russian KGB some of them were trained by the Cubans so we not only had to train them we also had to win their trust and when we started this that's a diverse set of potential dogma and or just habits a theory modernised if you will right is that what the there was there was a question of of learning new skills and there was a question about also about learning management capabilities there was also question of learning the importance of the media for when you do difficult and complex investigations there was a question about using digital resources but there was also fundamentally a question of just building trust and when we started this program none of the black officers wanted to be photographed with all these foreign trainers who were senior foreign intelligence officers when we finished that everyone wanted to be in the photograph and so this was a great South African success story but the President and the deputy president then reflected on what to do with his capacity and they appointed the ministerial task force to do this and we were asked to make recommendations to this Minister ministerial task force and one of the things which we did was we showed them a movie because you referenced the movie and the movie we showed them was the untouchables with Kevin Costner and Sean Connery which is still one of my favorite and and greatest movies and the story The Untouchables is about police corruption in Chicago and how in the Treasury Department a man called Eliot Ness put together a group of officers from which he selected from different places with clean hands to go after corruption during the Probie and this really captured the president's imagination and so he said that's what he want and Ella yeah okay so he said della one of the untouchables he wanted Eliot Ness exactly Al Capone's out there and and how many people were in that goodness so we asked that we we established the government then established decided to establish and this was passed as a law through Parliament the director of special operations the DSO which colloquy became known as the scorpions and it had a scorpion as a symbol for this unit and this became a standalone anti-corruption unit and the brilliant thing about it John was that the first intake of scorpion officers were all young black graduates many of them law graduates and at the time Janet Reno was the US Attorney General played a very crucial role she allowed half of the first intake of young cratchits to go to Quantico and to do the full FBI course in Quantico and this was the first group of foreign students who've ever been admitted to Quantico to do the full Quantico were you involved at what score's at that time yes sir and so you worked with President Mandela yes the set of the scorpions is untouchable skiing for the first time as a new democracy is emerging the landscape is certainly changing there's a transformation happening we all know the history laugh you don't watch Invictus probably great movie to do that you then worked with the Attorney General United States to cross-pollinate the folks in South Africa black officers law degrees Samar's fresh yes this unit with Quantico yes in the United States I had the privilege of attending the the graduation ceremony of the first of South African officers that completed the Quantico course and representing crow they on the day you had us relationships at that time to crawl across pollen I had the privilege of working with some of the best law enforcement officers and best intelligence officers that has come out of the u.s. services and they've been tremendous mentors in my career they've really shaped my thinking they've shaped my values and they've they've shaved my character so you're still under 30 at this time so give us a is that where this where are we in time now just about a 30 so you know around the nine late nineties still 90s yeah so client-server technologies there okay so also the story references Leonard McCarthy and these spy tapes what is this spy tape saga about it says you had a conversation with McCarthy me I'm thinking that a phone tap explain that spy tape saga what does it mean who's Lennon McCarthy explain yourself so so so Leonard McCarthy it's a US citizen today he served two terms as the vice president for institutional integrity at the World Bank which is the world's most important anti-corruption official he started his career as a prosecutor in South Africa many years ago and then became the head of the economic crimes division in the South African Justice Department and eventually became the head of the scorpions and many years after I've left Kroll and were no longer involved in in the work of the scorpions he texted me one evening expressing a concern and an anxiety that I had about the safety of his family and I replied to him with two text messages one was a Bible verse and the other one was a Latin saying and my advice name was follow the rule of law and put the safety of your family first and that was the advice I gave him so this is how I imagined the year I think of it the internet was just there this was him this was roundabout 2000 December 2007 okay so there was I phone just hit so text messaging Nokia phones all those big yeah probably more text message there so you sitting anywhere in London you get a text message from your friend yep later this past late tonight asking for help and advice and I gave him the best advice I can he unfortunately was being wiretapped and those wiretaps were subsequently published and became the subject of much controversy they've now been scrutinized by South Africa's highest court and the court has decided that those wiretaps are of no impact and of importance in the scheme of judicial decision-making and our unknown provenance and on and on unknown reliability they threw it out basically yeah they're basically that's the president he had some scandals priors and corruption but back to the tapes you the only involvement on the spy tapes was friend sending you a text message that says hey I'm running a corruption you know I'm afraid for my life my family what do I do and you give some advice general advice and that's it as there was there any more interactions with us no that's it that's it okay so you weren't like yeah working with it hey here's what we get strategy there was nothing that going on no other interactions just a friendly advice and that's what they put you I gave him my I gave him my best advice when you when you work in when you work as an investigator very much as and it's very similar in venture capital it's all about relationships and you want to preserve relationships for the long term and you develop deep royalties to its people particularly people with whom you've been through difficult situations as I have been with Leonard much earlier on when I was still involved in Kroll and giving advice to South African government on issues related to the scorpius so that that has a lot of holes and I did think that was kind of weird they actually can produce the actual tax I couldn't find that the spy tapes so there's a spy tape scandal out there your name is on out on one little transaction globbed on to you I mean how do you feel about that I mean you must've been pretty pissed when you saw that when you do it when when you do when you do investigative work you see really see everything and all kinds of things and the bigger the issues that you deal with the more frequently you see things that other people might find unusual I are you doing any work right now with c5 at South Africa and none whatsoever so I've I retired from my investigative Korea in 2014 I did terrific 20 years as an investigator during my time as investigator I came to understood the importance of digital and cyber and so at the end of it I saw an opportunity to serve a sector that historically have been underserved with capital which is cyber security and of course there are two areas very closely related to cyber security artificial intelligence and cloud and that's why I created c5 after I sold my investigator firm with five other families who equally believed in the importance of investing private capital to make a difference invest in private capital to help bring about innovation that can bring stability to the digital world and that's the mission of c-5 before I get to the heart news I want to drill in on the BBC stories I think that's really the focal point of you know why we're talking just you know from my standpoint I remember living as a young person in that time breaking into the business you know my 20s and 30s you had Live Aid in 1985 and you had 1995 the internet happened there was so much going on between those that decade 85 to 95 you were there I was an American so I didn't really have a lot exposure I did some work for IBM and Europe in 1980 says it's co-op student but you know I had some peak in the international world it must been pretty dynamic the cross-pollination the melting pot of countries you know the Berlin Wall goes down you had the cold war's ending you had apartheid a lot of things were going on around you yes so in that dynamic because if if the standard is you had links to someone you know talked about why how important it was that this melting pot and how it affected your relationships and how it looks now looking back because now you can almost tie anything to anything yes so I think the 90s was one of the most exciting periods of time because you had the birth of the internet and I started working on Internet related issues yet 20 million users today we have three and a half billion users and ten billion devices unthinkable at the time but in the wake of the internet also came a lot of changes as you say the Berlin Wall came down democracy in South Africa the Oslo peace process in the time that I worked in Kroll some of them made most important and damaging civil wars in Africa came to an end including the great war in the Congo peace came to Sudan and Angola the Ivory Coast so a lot of things happening and if you have a if you had a an international career at that time when globalization was accelerating you got to no a lot of people in different markets and both in crow and in my consulting business a key part of what it but we did was to keep us and Western corporations that were investing in emerging markets safe your credibility has been called in questions with this article and when I get to in a second what I want to ask you straight up is it possible to survive in the international theatre to the level that you're surviving if what they say is true if you if you're out scamming people or you're a bad actor pretty much over the the time as things get more transparent it's hard to survive right I mean talk about that dynamic because I just find it hard to believe that to be successful the way you are it's not a johnny-come-lately firms been multiple years operating vetted by the US government are people getting away in the shadows is it is is it hard because I almost imagine those are a lot of arbitrage I imagine ton of arbitrage that you that are happening there how hard or how easy it is to survive to be that shady and corrupt in this new era because with with with investigated with with intelligence communities with some terrific if you follow the money now Bitcoin that's a whole nother story but that's more today but to survive the eighties and nineties and to be where you are and what they're alleging I just what's your thoughts well to be able to attract capital and investors you have to have very high standards of governance and compliance because ultimately that's what investors are looking for and what investors will diligence when they make an investment with you so to carry the confidence of investors good standards of governance and compliance are of critical importance and raising venture capital and Europe is tough it's not like the US babe there's an abundance of venture capital available it's very hard Europe is under served by capital the venture capital invested in the US market is multiple of what we invest in Europe so you need to be even more focused on governance and compliance in Europe than you would be perhaps on other markets I think the second important point with Gmail John is that technology is brought about a lot of transparency and this is a major area of focus for our piece tech accelerator where we have startups who help to bring transparency to markets which previously did not have transparency for example one of the startups that came through our accelerator has brought complete transparency to the supply chain for subsistence farmers in Africa all the way to to the to the shelf of Walmart or a big grocery retailer in in the US or Europe and so I think technology is bringing a lot more more transparency we also have a global anti-corruption Innovation Challenge called shield in the cloud where we try and find and recognize the most innovative corporations governments and countries in the space so let's talk about the BBC story that hit 12 it says is a US military cloud the DoD Jedi contractor that's coming to award the eleventh hour safe from Russia fears over sensitive data so if this essentially the headline that's bolded says a technology company bidding for a Pentagon contract that's Amazon Web Services to store sensitive data has close partnerships with a firm linked to a sanctioned Russian oligarch the BBC has learned goes on to essentially put fear and tries to hang a story that says the national security of America is at risk because of c5u that's what we're talking about right now so so what's your take on this story I mean did you wake up and get an email said hey check out the BBC you're featured in and they're alleging that you have links to Russia and Amazon what Jon first I have to go I first have to do a disclosure I've worked for the BBC as an investigator when I was in Kroll and in fact I let the litigation support for the BBC in the biggest libel claim in British history which was post 9/11 when the BBC did a broadcast mistakenly accusing a mining company in Africa of laundering money for al-qaeda and so I represented the BBC in this case I was the manager hired you they hired me to delete this case for them and I'm I helped the BBC to reduce a libel claim of 25 million dollars to $750,000 so I'm very familiar with the BBC its integrity its standards and how it does things and I've always held the BBC in the highest regard and believed that the BBC makes a very important contribution to make people better informed about the world so when I heard about the story I was very disappointed because it seemed to me that the BBC have compromised the independence and the independence of the editorial control in broadcasting the story the reason why I say that is because the principal commentator in this story as a gentleman called John Wheeler who's familiar to me as a someone who's been trolling our firm on internet for the last year making all sorts of allegations the BBC did not disclose that mr. Weiler is a former Oracle executive the company that's protesting the Jedi bidding contract and secondly that he runs a lobbying firm with paid clients and that he himself often bid for government contracts in the US government context you're saying that John Wheeler who's sourced in the story has a quote expert and I did check him out I did look at what he was doing I checked out his Twitter he seems to be trying to socialise a story heavily first he needed eyes on LinkedIn he seems to be a consultant firm like a Beltway yes he runs a he runs a phone called in interoperability Clearing House and a related firm called the IT acquisition Advisory Council and these two organizations work very closely together the interoperability Clearing House or IC H is a consulting business where mr. Weiler acts for paying clients including competitors for this bidding contract and none of this was disclosed by the BBC in their program the second part of this program that I found very disappointing was the fact that the BBC in focusing on the Russian technology parks cocuwa did not disclose the list of skok of our partners that are a matter of public record on the Internet if you look at this list very closely you'll see c5 is not on there neither Amazon Web Services but the list of companies that are on there are very familiar names many of them competitors in this bidding process who acted as founding partners of skok about Oracle for example as recently as the 28th of November hosted what was described as the largest cloud computing conference in Russia's history at Skolkovo this is the this is the place which the BBC described as this notorious den of spies and at this event which Oracle hosted they had the Russian presidential administration on a big screen as one of their clients in Russia so some Oracle is doing business in Russia they have like legit real links to Russia well things you're saying if they suddenly have very close links with Skolkovo and so having a great many other Khayyam is there IBM Accenture cisco say Microsoft is saying Oracle is there so Skolkovo has a has a very distinguished roster of partners and if the BBC was fair and even-handed they would have disclosed us and they would have disclosed the fact that neither c5 nor Amazon feature as Corcovado you feel that the BBC has been duped the BBC clearly has been duped the program that they broadcasted is really a parlor game of six degrees of separation which they try to spun into a national security crisis all right so let's tell us John while ago you're saying John Wyler who's quoted in the story as an expert and by the way I read in the story my favorite line that I wanted to ask you on was there seems to be questions being raised but the question is being raised or referring to him so are you saying that he is not an expert but a plant for the story what's what's his role he's saying he works for Oracle or you think do you think he's being paid by Oracle like I can't comment on mr. Wireless motivation what strikes me is the fact that is a former Oracle executive what's striking is that he clearly on his website for the IC H identifies several competitors for the Jedi business clients and that all of this should have been disclosed by the BBC rather than to try and characterize and portray him as an independent expert on this story well AWS put out a press release or a blog post essentially hum this you know you guys had won it we're very clear and this I know it goes to the top because that's how Amazon works nothing goes out until it goes to the top which is Andy chassis and the senior people over there it says here's the relationship with c5 and ATS what school you use are the same page there but also they hinted the old guard manipulation distant I don't think they use the word disinformation campaign they kind of insinuate it and that's what I'm looking into I want to ask you are you part are you a victim of a disinformation campaign do you believe that you're not a victim being targeted with c5 as part of a disinformation campaign put on by a competitor to AWS I think what we've seen over the course of this last here is an enormous amount of disinformation around this contract and around this bidding process and they've a lot of the information that has been disseminated has not only not been factual but in some cases have been patently malicious well I have been covering Amazon for many many years this guy Tom Wyler is in seems to be circulating multiple reports invested in preparing for this interview I checked Vanity Fair he's quoted in Vanity Fair he's quoted in the BBC story and there's no real or original reporting other than those two there's some business side our article which is just regurgitating the Business Insider I mean the BBC story and a few other kind of blog stories but no real original yes no content don't so in every story that that's been written on this subject and as you say most serious publication have thrown this thrown these allegations out but in the in those few instances where they've managed to to publish these allegations and to leverage other people's credibility to their advantage and leverage other people's credibility for their competitive advantage John Wheeler has been the most important and prominent source of the allegations someone who clearly has vested commercial interests someone who clearly works for competitors as disclosed on his own website and none of this has ever been surfaced or addressed I have multiple sources have confirmed to me that there's a dossier that has been created and paid for by a firm or collection of firms to discredit AWS I've seen some of the summary documents of that and that is being peddled around to journalists we have not been approached yet I'm not sure they will because we actually know the cloud what cloud computing is so I'm sure we could debunk it by just looking at it and what they were putting fors was interesting is this an eleventh-hour a desperation attempt because I have the Geo a report here that was issued under Oracle's change it says there are six conditions why we're looking at one sole cloud although it's not a it's a multiple bid it's not an exclusive to amazon but so there's reasons why and they list six service levels highly specialized check more favorable terms and conditions with a single award expected cause of administration of multiple contracts outweighs the benefits of multiple awards the projected orders are so intricately related that only a single contractor can reasonably be perform the work meaning that Amazon has the only cloud that can do that work now I've reported on the cube and it's looking angle that it's true there's things that other clouds just don't have anyone has private they have the secret the secret clouds the total estimated value of the contract is less than the simplified acquisition threshold or multiple awards would not be in the best interest this is from them this is a government report so it seems like there's a conspiracy against Amazon where you are upon and in in this game collect you feel that collateral damage song do you do you believe that to be true collateral damage okay well okay so now the the John Wheeler guys so investigate you've been an investigator so you mean you're not you know you're not a retired into this a retired investigator you're retired investigated worked on things with Nelson Mandela Kroll Janet Reno Attorney General you've vetted by the United States government you have credibility you have relationships with people who have have top-secret clearance all kinds of stuff but I mean do you have where people have top-secret clearance or or former people who had done well we have we have the privilege of of working with a very distinguished group of senior national security leaders as operating partisan c5 and many of them have retained their clearances and have been only been able to do so because c5 had to pass through a very deep vetting process so for you to be smeared like this you've been in an investigative has you work at a lot of people this is pretty obvious to you this is like a oh is it like a deep state conspiracy you feel it's one vendor - what is your take and what does collateral damage mean to you well I recently spoke at the mahkum conference on a session on digital warfare and one of the key points I made there was that there are two things that are absolutely critical for business leaders and technology leaders at this point in time one we have to clearly say that our countries are worth defending we can't walk away from our countries because the innovation that we are able to build and scale we're only able to do because we live in democracies and then free societies that are governed by the rule of law the second thing that I think is absolutely crucial for business leaders in the technology community is to accept that there must be a point where national interest overrides competition it must be a point where we say the benefit and the growth and the success of our country is more important to us than making commercial profits and therefore there's a reason for us either to cooperate or to cease competition or to compete in a different way what might takes a little bit more simple than that's a good explanation is I find these smear campaigns and fake news and I was just talking with Kara Swisher on Twitter just pinging back and forth you know either journalists are chasing Twitter and not really doing the original courting or they're being fed stories if this is truly a smear campaign as being fed by a paid dossier then that hurts people when families and that puts corporate interests over the right thing so I think I a personal issue with that that's fake news that's just disinformation but it's also putting corporate inches over over families and people so I just find that to be kind of really weird when you say collateral damage earlier what did you mean by that just part of the campaign you personally what's what's your view okay I think competition which is not focused on on performance and on innovation and on price points that's competition that's hugely destructive its destructive to the fabric of innovation its destructive of course to the reputation of the people who fall in the line of sight of this kind of competition but it's also hugely destructive to national interest Andrae one of the key stories here with the BBC which has holes in it is that the Amazon link which we just talked about but there's one that they bring up that seems to be core in all this and just the connections to Russia can you talk about your career over the career from whether you when you were younger to now your relationship with Russia why is this Russian angle seems to be why they bring into the Russia angle into it they seem to say that c-5 Cable has connections they call deep links personal links into Russia so to see what that so c5 is a venture capital firm have no links to Russia c5 has had one individual who is originally of Russian origin but it's been a longtime Swiss resident and you national as a co investor into a enterprise software company we invested in in 2015 in Europe we've since sold that company but this individual Vladimir Kuznetsov who's became the focus of the BBC's story was a co investor with us and the way in which we structure our investment structures is that everything is transparent so the investment vehicle for this investment was a London registered company which was on the records of Companies House not an offshore entity and when Vladimir came into this company as a co investor for compliance and regulatory purposes we asked him to make his investment through this vehicle which we controlled and which was subject to our compliance standards and completely transparent and in this way he made this investment now when we take on both investors and Co investors we do that subject to very extensive due diligence and we have a very robust and rigorous due diligence regime which in which our operating partners who are leaders of great experience play an important role in which we use outside due diligence firms to augment our own judgment and to make sure we have all the facts and finally we also compare notes with other financial institutions and peers and having done that with Vladimir Kuznetsov when he made this one investment with us we reached the conclusion that he was acting in his own right as an independent angel investor that his left renova many years ago as a career executive and that he was completely acceptable as an investor so that you think that the BBC is making an inaccurate Association the way they describe your relationship with Russia absolutely the the whole this whole issue of the provenance of capital has become of growing importance to the venture capital industry as you and I discussed earlier with many more different sources of capital coming out of places like China like Russia Saudi Arabia other parts of the world and therefore going back again to you the earlier point we discussed compliance and due diligence our critical success factors and we have every confidence in due diligence conclusions that we reached about vladimir quits net source co-investment with us in 2015 so I did some digging on c5 razor bidco this was the the portion of the company in reference to the article I need to get your your take on this and they want to get you on the record on this because it's you mentioned I've been a law above board with all the compliance no offshore entities this is a personal investment that he made Co investment into an entity you guys set up for the transparency and compliance is that true that's correct no side didn't see didn't discover this would my my children could have found this this this company was in a transparent way on the records in Companies House and and Vladimir's role and investment in it was completely on the on the public record all of this was subject to financial conduct authority regulation and anti money laundering and no your client standards and compliance so there was no great big discovery this was all transparent all out in the open and we felt very confident in our due diligence findings and so you feel very confident Oh issue there at all special purpose none whatsoever is it this is classic this is international finance yes sir so in the venture capital industry creating a special purpose vehicle for a particular investment is a standard practice in c-five we focus on structuring those special-purpose vehicles in the most transparent way possible and that was his money from probably from Russia and you co invested into this for this purpose of doing these kinds of deals with Russia well we just right this is kind of the purpose of that no no no this so in 2015 we invested into a European enterprise software company that's a strategic partner of Microsoft in Scandinavian country and we invested in amount of 16 million pounds about at the time just more than 20 million dollars and subsequent in August of that year that Amir Kuznetsov having retired for nova and some time ago in his own right as an angel investor came in as a minority invest alongside us into this investment but we wanted to be sure that his investment was on our control and subject to our compliance standards so we requested him to make his investment through our special purpose vehicle c5 raised a bit co this investment has since been realized it's been a great success and this business is going on to do great things and serve great clients it c5 taking russian money no see if I was not taking Russian money since since the onset of sanctions onboarding Russian money is just impossible sanctions have introduced complexity and have introduced regulatory risk related to Russian capital and so we've taken a decision that we will not and we can't onboard Russian capital and sanctions have also impacted my investigative career sanctions have also completely changed because what the US have done very effectively is to make sanctions a truly global regime and in which ever country are based it doesn't really matter you have to comply with US sanctions this is not optional for anybody on any sanctions regime including the most recent sanctions on Iran so if there are sanctions in place you can't touch it have you ever managed Russian oligarchs money or interests at any time I've never managed a Russian oligarchs money at any point in time I served for a period of a year honest on the board of a South African mining company in which Renova is a minority invest alongside an Australian company called South 32 and the reason why I did this was because of my support for African entrepreneurship this was one of the first black owned mining companies in South Africa that was established with a British investment in 2004 this business have just grown to be a tremendous success and so for a period of a year I offered to help them on the board and to support them as they as they looked at how they can grow and scale the business I have a couple more questions Gabe so I don't know if you wanna take a break you want to keep let's take a break okay let's take a quick break do a quick break I think that's great that's the meat of it great job by the way fantastic lady here thanks for answering those questions the next section I want to do is compliment